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THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about the INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679.THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about the INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. THE WEB CONFERENCE 2020 The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue. THE WEB CONFERENCE 2020 Thursday, April 9, 2020. Registration Type. Rate. Special Track Only Package on. Wednesday, April 22, 2020. 6,000. Special Track Package include: - Entry to Keynote Speech and Opening Ceremony. - Entry to AIoT, Web@30 and W3C events.PAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron ONE DETECTOR TO RULE THEM ALL: TOWARDS A GENERAL DEEPFAKE The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. USER TRACKING IN THE POST-COOKIE ERA: HOW WEBSITES BYPASS During the past couple of years, mostly as a result of GDPR and CCPA, websites have started to present users with cookie consent banners. These banners are web forms where the users can state their preference and declare which cookies they would like to accept, if any at all. EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. Konstan THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about thePAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. KEYNOTES | THE WEB CONFERENCE He was member of the IJCAI Board of Trustees, President of IJCAI, President of KR, Inc., Advisory Board member of KR, Inc., Steering Committee of the CONTEXT conference. Fausto has covered all the spectrum from theory to technology transfer and innovation. He was involved in more than 20 international R&D projects, including severalEC projects.
INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about thePAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. KEYNOTES | THE WEB CONFERENCE He was member of the IJCAI Board of Trustees, President of IJCAI, President of KR, Inc., Advisory Board member of KR, Inc., Steering Committee of the CONTEXT conference. Fausto has covered all the spectrum from theory to technology transfer and innovation. He was involved in more than 20 international R&D projects, including severalEC projects.
INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION In this paper, we propose a novel Graph Topic Neural Network (GTNN) model to mine latent topic semantic for interpretable document representation learning, taking into account the document-document, document-word and word-word relationships in the graph.We also show that our model can be viewed as semi- amortized inference forrelational topic
WORKSHOPS | THE WEB CONFERENCE LocWeb2021 is a full day workshop at The Web Conference 2021. It will run for the 11th time with evolving topics around location-aware information access, Web architecture, spatial social computing, and social good. It is designed as a meeting place for researchers around the location topic at FM^2: FIELD-MATRIXED FACTORIZATION MACHINES FOR CTR In this paper, we propose a novel way to model the field information effectively and efficiently, we called it Field-matrixed Factorization Machines (FmFM, or FM^2), which is a direct improvement of FwFMs. We also proposed a new explanation of FMs and FwFMs within the FmFMs framework, and compared the FFMs and FmFMs. Besides pruning the cross DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron FINN: FEEDBACK INTERACTIVE NEURAL NETWORK FOR INTENT Therefore, we propose a feedback interactive neural network (FINN) to estimate user’s potential search intent more accurately, by making full use of the feedback interaction with the following three parts: 1) Both positive feedback (PF) and negative REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. Konstan THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about thePAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. KEYNOTES | THE WEB CONFERENCE He was member of the IJCAI Board of Trustees, President of IJCAI, President of KR, Inc., Advisory Board member of KR, Inc., Steering Committee of the CONTEXT conference. Fausto has covered all the spectrum from theory to technology transfer and innovation. He was involved in more than 20 international R&D projects, including severalEC projects.
INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey.THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about thePAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. KEYNOTES | THE WEB CONFERENCE He was member of the IJCAI Board of Trustees, President of IJCAI, President of KR, Inc., Advisory Board member of KR, Inc., Steering Committee of the CONTEXT conference. Fausto has covered all the spectrum from theory to technology transfer and innovation. He was involved in more than 20 international R&D projects, including severalEC projects.
INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION In this paper, we propose a novel Graph Topic Neural Network (GTNN) model to mine latent topic semantic for interpretable document representation learning, taking into account the document-document, document-word and word-word relationships in the graph.We also show that our model can be viewed as semi- amortized inference forrelational topic
WORKSHOPS | THE WEB CONFERENCE LocWeb2021 is a full day workshop at The Web Conference 2021. It will run for the 11th time with evolving topics around location-aware information access, Web architecture, spatial social computing, and social good. It is designed as a meeting place for researchers around the location topic at FM^2: FIELD-MATRIXED FACTORIZATION MACHINES FOR CTR In this paper, we propose a novel way to model the field information effectively and efficiently, we called it Field-matrixed Factorization Machines (FmFM, or FM^2), which is a direct improvement of FwFMs. We also proposed a new explanation of FMs and FwFMs within the FmFMs framework, and compared the FFMs and FmFMs. Besides pruning the cross DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron FINN: FEEDBACK INTERACTIVE NEURAL NETWORK FOR INTENT Therefore, we propose a feedback interactive neural network (FINN) to estimate user’s potential search intent more accurately, by making full use of the feedback interaction with the following three parts: 1) Both positive feedback (PF) and negative REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. KonstanTHE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. THE WEB CONFERENCE 2020 The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.PAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. NETWORK OF TENSOR TIME SERIES The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. MINING DUAL EMOTION FOR FAKE NEWS DETECTION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. DYMOND: DYNAMIC MOTIF-NODES NETWORK GENERATIVE MODEL DYMOND: DYnamic MOtif-NoDes Network Generative Model. The graph structure in dynamic networks changes rapidly. By leveraging temporal information inherent in network connections, models of these dynamic networks can be constructed to analyze how their structure changes over time. However, most existing generative models for temporalgraphs grow
FINN: FEEDBACK INTERACTIVE NEURAL NETWORK FOR INTENT Therefore, we propose a feedback interactive neural network (FINN) to estimate user’s potential search intent more accurately, by making full use of the feedback interaction with the following three parts: 1) Both positive feedback (PF) and negative EFFICIENT NON-SAMPLING KNOWLEDGE GRAPH EMBEDDING The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
DEBIASING CAREER RECOMMENDATIONS WITH NEURAL FAIR We develop neural fair collaborative filtering (NFCF), a practical framework for mitigating gender bias in recommending career-related sensitive items (e.g. jobs, academic concentrations, or courses of study) using a pre-training and fine-tuning approach to neural collaborative filtering, augmented with bias correction techniques. EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. KonstanTHE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. UNSUPERVISED LIFELONG LEARNING WITH CURRICULA Unsupervised Lifelong Learning with Curricula. Lifelong machine learning (LML) has extensively driven the development of web applications, enabling the learning systems deployed on web servers to deal with a sequence of tasks in an incremental fashion. Such systems can retain knowledge from learned tasks in a knowledge base andseamlessly
GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. THE WEB CONFERENCE 2020 The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.PAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. NETWORK OF TENSOR TIME SERIES The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. MINING DUAL EMOTION FOR FAKE NEWS DETECTION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. DYMOND: DYNAMIC MOTIF-NODES NETWORK GENERATIVE MODEL DYMOND: DYnamic MOtif-NoDes Network Generative Model. The graph structure in dynamic networks changes rapidly. By leveraging temporal information inherent in network connections, models of these dynamic networks can be constructed to analyze how their structure changes over time. However, most existing generative models for temporalgraphs grow
FINN: FEEDBACK INTERACTIVE NEURAL NETWORK FOR INTENT Therefore, we propose a feedback interactive neural network (FINN) to estimate user’s potential search intent more accurately, by making full use of the feedback interaction with the following three parts: 1) Both positive feedback (PF) and negative EFFICIENT NON-SAMPLING KNOWLEDGE GRAPH EMBEDDING The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
DEBIASING CAREER RECOMMENDATIONS WITH NEURAL FAIR We develop neural fair collaborative filtering (NFCF), a practical framework for mitigating gender bias in recommending career-related sensitive items (e.g. jobs, academic concentrations, or courses of study) using a pre-training and fine-tuning approach to neural collaborative filtering, augmented with bias correction techniques. EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. Konstan THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. THE WEB CONFERENCE 2020VOLUNTEERSHIPCALL FOR CONTRIBUTIONSPOLICYPRESS RELEASECOMMITTEESBECOME A SPONSOR The Web Conference 2020 Local Organizing Committees has been working very hard behind the scenes in making the 2020 edition a safe and successful one in considering of that the COVID-19 is an extraordinary global public health issue.THE WEB CONFERENCE
The Web Conference was to be held in Ljubljana, the capital of Slovenia, in the heart of Europe. Due to the current health situation worldwide, we should offer the best possible user experience as a fully virtual conference. We invite you to join us from April 12 to April 23, 2021. In our program you will find first week of exclusiveworkshops
THE WEB CONFERENCE
The Web Conference (formerly www conference) is a yearly international conference on the topic of the future directions of the World Wide Web.. The conference series began in 1994 at CERN and has been organized from 1994 to 2021 by the International World Wide Web Conferences Committee (IW3C2).. The Conference aims to provide the world with a premier forum for discussion and debate about theTHEWEBCONF 2022
The Web Conference is back in Lyon in 2022 ! After the 2021 edition in Ljubljana, The Web Conference 2022 will be hosted by Université de Lyon. We are looking forward to meet you for the next edition ! The Web Conference social media will soon be updated with the 2022 logo and more information about this next edition. TheWebConf 2021 survey. REVISITING THE EVALUATION PROTOCOL OF KNOWLEDGE GRAPH Completion methods learn models to infer missing (subject, predicate, object) triples in knowledge graphs, a task known as link prediction. The training phase is based on samples of positive triples and their negative counterparts. INCREMENTAL SPATIO-TEMPORAL GRAPH LEARNING FOR ONLINE Incremental Spatio-Temporal Graph Learning for Online Query-POI Matching. Query and Point-of-Interest (POI) matching, aiming at recommending the most relevant POIs from partial query keywords, has become one of the most essential functions in online navigation and ride-hailing applications. Existing methods for query-POI matching,such as
DEEPFEC: ENERGY CONSUMPTION PREDICTION UNDER REAL-WORLD The status of air pollution is serious all over the world. Analysing and predicting vehicle energy consumption becomes a major concern. Vehicle energy consumption depends not only on speed but also on a number of external factors such as road topology, traffic, driving style, etc. Obtaining the cost for each link (i.e., link energy consumption) in road networks plays a key role in energy LORENTZIAN GRAPH CONVOLUTIONAL NEURAL NETWORKS In this paper, we propose a novel hyperbolic GCN named Lorentzian graph convolutional network (LGCN), which rigorously guarantees the learned node features follow the hyperbolic geometry. Specifically, we rebuild the graph operations of hyperbolic GCNs with Lorentzian version, e.g., the feature transformation and non-linear activation. ROBUST ANDROID MALWARE DETECTION AGAINST ADVERSARIAL In this paper, we propose a novel robust Android malware detection approach that can resist adversarial examples without requiring their instances or knowledge by jointly investigating malware detection and adversarial example defenses. More precisely, our approach employs a new VAE (variational autoencoder) and an MLP (multi-layer perceptron GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. THE WEB CONFERENCE 2020 The Web Conference 2020 will be taking place in Taipei International Convention Center (TICC). The TICC is located at No. 1, Section 5, Xinyi Road, Xinyi District, Taipei City 11049, just a short walk from the one of the world’s iconic tower building Taipei 101 and MRT Taipei 101/ World Trade Centre Station. THE WEB CONFERENCE 2020 Thursday, April 9, 2020. Registration Type. Rate. Special Track Only Package on. Wednesday, April 22, 2020. 6,000. Special Track Package include: - Entry to Keynote Speech and Opening Ceremony. - Entry to AIoT, Web@30 and W3C events.PAPERS PROGRAM
Title. Authors. 10:00-11:40. economics. REST: Relational Event-driven Stock Trend Forecasting. Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin and Tie-Yan Liu. Exploring the Scale-Free Nature of Stock Markets: Hyperbolic Graph Learning for Algorithmic Trading. Ramit Sawhney, Shivam Agarwal, Arnav Wadhwa and Rajiv Shah. KEYNOTES | THE WEB CONFERENCE Abstract: The Web has transformed our lives by allowing us to transcend temporal, geographical and cultural borders. It is a fact that we get exposed daily to a seemingly unbound amount of diversity and, therefore, of opportunities; think for instance of the emergence of global digital platforms. GRAPH TOPIC NEURAL NETWORK FOR DOCUMENT REPRESENTATION In this paper, we propose a novel Graph Topic Neural Network (GTNN) model to mine latent topic semantic for interpretable document representation learning, taking into account the document-document, document-word and word-word relationships in the graph.We also show that our model can be viewed as semi- amortized inference forrelational topic
EFFICIENT KNOWLEDGE GRAPH EMBEDDING WITHOUT NEGATIVE Knowledge Graph (KG) is a flexible structure that is able to describe the complex relationship between data entities. Currently, most KG embedding models are trained based on negative sampling, i.e., the model aims to maximize some similarity of the connected entities in the KG, while minimizing the similarity of the sampled disconnectedentities.
REINFORCEMENT RECOMMENDATION WITH USER MULTI-ASPECT The Web Conference is announcing latest news and developments biweekly or on a monthly basis. We respect The General Data Protection Regulation 2016/679. SIXTH INTERNATIONAL WORLD WIDE WEB CONFERENCE (V1.57) April 7-11, 1997 Santa Clara, California USA The theme of this year's conference was accessibility; the slogan was: Everyone Everything Connected Registration: Contact info for questions concerning registration, receipts, accounting, etc.: EXPLORING THE FILTER BUBBLE: THE EFFECT OF USING Exploring the Filter Bubble: The Effect of Using Recommender Systems on Content Diversity Tien T. Nguyen Pik-Mai Hui F. Maxwell Harper Loren Terveen Joseph A. Konstan CROWD FRAUD DETECTION IN INTERNET ADVERTISING Crowd Fraud Detection in Internet Advertising Tian Tian†, Jun Zhu†, Fen Xia‡, Xin Zhuang‡, Tong Zhang‡ †State Key Lab of Intelligent Technology & Systems; Tsinghua National TNLIST Lab Department of Computer Science & Technology, Tsinghua University, Beijing 100084, ChinaSkip to list
HISTORY OF THEWEBCONF SERIES The WORLD WIDE WEB was first conceived in 1989 by TIM BERNERS-LEEat CERN
in Geneva, Switzerland. The first conference of the series, WWW1, was held at CERN in 1994 and organized by ROBERT CAILLIAU . The INTERNATIONAL WORLD WIDE WEB CONFERENCE COMMITTEE (IW3C2) was founded by JOSEPH HARDIN and ROBERT CAILLIAU later in 1994 and has been responsible for the conference series ever since. Except for 1994 and 1995 when two conferences were held each year, WWW became an annual event held in April or May. The location of the conference rotates among America, Europe, and Asia-Pacific. In 2001 the conference designator changed from a number (1 through 10) to the year it is held; i.e., WWW11 became known as WWW2002, and so on. Starting in 2018, The brand of the conference has been changed and the series is now named THE WEB CONFERENCE or in brief THEWEBCONF and starting in 2022, the conference will become an ACM/SIGWEB event and the rotation between the three geographical areas will no longer bethe rule.
------------------------- Below are informations about past conferences in the series.Toggle list menu
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------------------------- The First International WWW ConferenceHOST:
* CERN
DATE:
May 25-27, 1994
VENUE:
CERN, Geneva, Switzerland/France No web site available No proceedings available ------------------------- The Second International WWW ConferenceHOST:
* SDG at UIUC
* OSF
* CERN
DATE:
October 17-20, 1994
VENUE:
Ramada-Congress Hotel, 520 South Michigan Avenue, Chicago,Illinois, USA
Web site
Proceedings
------------------------- The Third International WWW ConferenceHOST:
* Fraunhofer Gesellschaft/Institute for Graphic Design (FhG/IGD)DATE:
April 10-14, 1995
VENUE:
Darmstadt, Germany
No web site available No proceedings available ------------------------- The Fourth International WWW ConferenceHOST:
* The MIT Laboratory for Computer Science * the OSF Research Institute* W3C
DATE:
December 11-14, 1995VENUE:
Boston Marriott Copley Place, and at the Hynes Convention CenterWeb site
No proceedings available ------------------------- The Fifth International WWW ConferenceHOST:
* INRIA
* ERCIM
* W3C
DATE:
May 6-10, 1996
VENUE:
CNIT-Paris La Défense, FranceWeb site
Proceedings
------------------------- The Sixth International WWW ConferenceHOST:
* Stanford University * Stanford Linear Accelerator Center (SLAC)DATE:
April 7-11, 1997
VENUE:
Santa Clara Convention Center, Santa Clara, California USAWeb site
Proceedings
------------------------- The Seventh International WWW ConferenceHOST:
* Consortium of Southern Cross University & PartnersDATE:
April 14-18, 1998
VENUE:
Convention & Exhibition Center, Brisbane, Australia No web site available No proceedings available ------------------------- The Eighth International WWW ConferenceHOST:
* NRC -CNRC
DATE:
May 11-14, 1999
VENUE:
Toronto Convention Centre, Toronto, CanadaWeb site
No proceedings available ------------------------- The Ninth International WWW ConferenceHOST:
* Centre for Mathematics and Computer Science (CWI)DATE:
May 15 - 19, 2000
VENUE:
Amsterdam Convention Centre, Amsterdam, The NetherlandsWeb site
Proceedings
------------------------- The Tenth International WWW ConferenceHOST:
* The Chinese University of Hong Kong * The University of Hong Kong * The Hong Kong University of Science and Technology * The Hong Kong Productivity Council * The The Hong Kong Information Technology Federation * The The Hong Kong Web Symposium Consortium Ltd * The Hong Kong Computer SocietyDATE:
May 1-5, 2001
VENUE:
Hong Kong Convention and Exhibition CenterWeb site
Proceedings
------------------------- The Eleventh International WWW ConferenceDATE:
May 6-11, 2002
VENUE:
Honolulu, Hawaii, USA No web site availableProceedings
------------------------- The Twelfth International WWW ConferenceHOST:
* Computer and Automation Research Institute of the Hungarian Academy of Sciences (MTA SZTAKI)DATE:
20-24 May, 2003
VENUE:
Budapest Convention Center, Budapest, HungaryWeb site
Proceedings
------------------------- The Thirteenth International WWW ConferenceDATE:
May 17-22, 2004
VENUE:
New York, USA
No web site availableProceedings
------------------------- The Fourteenth International WWW ConferenceHOST:
* Keio University
DATE:
May 10-14, 2005
VENUE:
Makuhari Messe (Nippon Convention Center), Chiba, JapanWeb site
Proceedings
------------------------- The Fifteenth International WWW ConferenceHOST:
* School of Electronics and Computer Science (ECS) at the Universityof Southampton
* BCS
* ACM
DATE:
May 23-26, 2006
VENUE:
Edinburgh International Conference Centre, Edinburgh, ScotlandWeb site
Proceedings
------------------------- The Sixteenth International WWW ConferenceHOST:
* University of CalgaryDATE:
May 8-12, 2007
VENUE:
Fairmont Banff Springs Hotel, Banff, Alberta, CanadaWeb site
Proceedings
------------------------- The Seventeenth International WWW ConferenceHOST:
* Beihang UniversityDATE:
April 21-25, 2008
VENUE:
Beijing International Convention Center, Beijing, ChinaWeb site
Proceedings
------------------------- The Eighteenth International WWW ConferenceHOST:
* Universidad Politécnica de Madrid (UPM) * Madrid municipalityDATE:
April 20-24, 2009
VENUE:
Palacio Municipal de Congresos, Madrid, SpainWeb site
Proceedings
------------------------- The Nineteenth International WWW ConferenceHOST:
* University of North Carolina at Chapel HillDATE:
April 26-30, 2010
VENUE:
Raleigh Convention Center, Raleigh, North Carolina, USA No web site availableProceedings
------------------------- The Twentyth International WWW ConferenceHOST:
* International Institute of Information Technology BangaloreDATE:
March 28 - April 1st, 2010VENUE:
Hyderabad International Convention Centre, Hyderabad, IndiaWeb site
Proceedings
------------------------- The Twenty First International WWW ConferenceHOST:
* Université de LyonDATE:
April 16-20, 2012
VENUE:
Lyon Convention Centre, Lyon, FranceWeb site
Proceedings
------------------------- The Twenty Second International WWW ConferenceHOST:
* Brazilian Internet Steering Committee * Brazilian Network Information CenterDATE:
May 13-17, 2013
VENUE:
Windsor Barra Hotel, Rio de Janeiro, BrazilWeb site
Proceedings
------------------------- The Twenty Third International WWW ConferenceHOST:
* Korea Advanced Institute of Science and Technology (KAIST) * Korean Agency for Technology and Standards (KATS)DATE:
April 7-11, 2014
VENUE:
Coex, Gangnam, Seoul, KoreaWeb site
Proceedings
------------------------- The Twenty Fourth International WWW ConferenceHOST:
* O.I.C. – International Congress Organization - Florence - ItalyDATE:
May 18-22, 2015
VENUE:
Fortezza da Basso, Florence, ItalyWeb site
Proceedings
------------------------- The Twenty Fifth International WWW ConferenceHOST:
* Université du Québec à Montréal (UQAM)DATE:
April 11-15, 2016
VENUE:
Palais des congrès, Montreal, CanadaWeb site
Proceedings
------------------------- The Twenty Sixth International WWW ConferenceHOST:
* W3Events Pty Ltd
DATE:
April 3-7, 2017
VENUE:
Perth Convention and Exhibition Centre, Perth, Western AustraliaWeb site
Proceedings
------------------------- The Twenty Seventh International WWW ConferenceHOST:
* Université de LyonDATE:
April 23-27, 2018
VENUE:
Lyon Convention Centre, Lyon, FranceWeb site
Proceedings
------------------------- The Twenty Eighth International WWW ConferenceHOST:
* Web4Good
DATE:
May 13-17 2019
VENUE:
Hyatt Regency Hotel, San Francisco, California, USAWeb site
Proceedings
------------------------- The Twenty Ninth International WWW ConferenceHOST:
* Academia Sinica
DATE:
April 20-24, 2020
VENUE:
Taipei International Convention Center, Xinyi District, Taipei _Moved on-line due to Covid-19 crisis_Web site
Proceedings
------------------------- The Thirtieth International WWW ConferenceHOST:
* Jozef Stefan InstituteDATE:
April 19-23, 2021
VENUE:
Ljubljana, Slovenia
_Moved on-line due to Covid-19 crisis_Web site
Proceedings
------------------------- -------------------------Details
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