{"id":1219,"date":"2022-01-28T00:25:26","date_gmt":"2022-01-28T00:25:26","guid":{"rendered":"https:\/\/www.wsdm-conference.org\/2022\/?post_type=mp-event&p=1219"},"modified":"2022-04-08T08:41:58","modified_gmt":"2022-04-08T15:41:58","slug":"poster-session-2","status":"publish","type":"mp-event","link":"http:\/\/www.wsdm-conference.org\/2022\/timetable\/event\/poster-session-2\/","title":{"rendered":"Poster Session #2"},"content":{"rendered":"\n

#1 Web mining \/ Web Search (III)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
MAVE: A Product Dataset for Multi-source Attribute Value Extraction<\/td>Li Yang (Google Research); Qifan Wang (Google Research)*; Zac Yu (Google); Anand Kulkarni (Google); Sumit Sanghai (Google LLC); Bin Shu (Google); Jonathan Elsas (Google); Bhargav Kanagal (Google)<\/td><\/tr>
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning<\/td>Xiaoyun Zhao (Sichuan University); Ning Yang (Sichuan University)*; Philip S Yu (UIC)<\/td><\/tr>
Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization<\/td>Shiyin Lu (Nanjing University)*; Yu-Hang Zhou (Alibaba Group); Jing-Cheng Shi (Nanjing University; Alibaba Group); wenya zhu (Alibaba); Qingtao Yu (Alibaba); Qing-Guo Chen (Alibaba); Qing Da (Alibaba Group); Lijun Zhang (Nanjing University)<\/td><\/tr>
Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce<\/td>Xuesi Wang (Alibaba); Guangda Huzhang (Alibaba); Qianying Lin (Alibaba)*; Qing Da (Alibaba Group)<\/td><\/tr>
Graph Collaborative Reasoning<\/td>Hanxiong Chen (Rutgers University)*; Yunqi Li (Rutgers University); Shaoyun Shi (Tsinghua University); Shuchang Liu (Rutgers University); He Zhu (Rutgers University); Yongfeng Zhang (Rutgers University)<\/td><\/tr>
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation<\/td>Yankai Chen (The Chinese University of Hong Kong)*; Menglin Yang (The Chinese University of Hong Kong); Yingxue Zhang (Huawei Technologies Canada); Mengchen Zhao (Huawei Noah’s Ark Lab); Ziqiao Meng (Chinese University of Hong Kong); Jianye Hao (Huawei Noah’s Ark Lab); Irwin King (The Chinese University of Hong Kong)<\/td><\/tr>
Retrieving Black-box Optimal Images from External Databases<\/td>Ryoma Sato (Kyoto University)*<\/td><\/tr>
MtCut: A Multi-Task Framework for Ranked List Truncation<\/td>Jianxin Li (Beihang University)*; Wang Dong (Beihang University); Tianchen Zhu (Beihang University); Qishan Zhu (Beihang University); Yuxin Wen (Beihang University); Piao Hongming (Beihang University)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#2 Web mining (III)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
MAF: A General Matching and Alignment Framework for Multimodal Named Entity Recognition<\/td>Bo Xu (Donghua University)*; Shizhou Huang (Donghua University); Chaofeng Sha (Fudan University); Hongya Wang (Donghua University)<\/td><\/tr>
A Peep into the Future: Adversarial Future Encoding in Recommendation<\/td>Ruobing Xie (WeChat Search Application Department, Tencent)*; Shaoliang Zhang (Tencent); Rui Wang (Tencent); Feng Xia (WeChat Search Application Department, Tencent); Leyu Lin (WeChat Search Application Department, Tencent)<\/td><\/tr>
Variational User Modeling with Slow and Fast Features<\/td>Ghazal Fazelnia (Spotify)*; Eric Simon (Spotify); Ian Anderson (Spotify); Benjamin Carterette (Spotify); Mounia Lalmas (Spotify)<\/td><\/tr>
Scalable Graph Topology Learning via Spectral Densification<\/td>Yongyu Wang (Michigan Technological University); Zhiqiang Zhao (Stevens Institute of Technology); Zhuo Feng (Stevens Institute of Technology)*<\/td><\/tr>
Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks<\/td>Zihan Liu (Westlake University)*; Yun Luo (Westlake university); Zelin Zang (Westlake University); Stan Z. Li (Westlake University)<\/td><\/tr>
DAME: Domain Adaptation for Matching Entities<\/td>Mohamed Trabelsi (Lehigh University)*; Jeff Heflin (Lehigh University); Jin Cao (Nokia Bell Labs)<\/td><\/tr>
Wikipedia Reader Navigation: When Synthetic Data is Enough<\/td>Akhil Arora (EPFL)*; Martin Gerlach (Wikimedia Foundation); Tiziano Piccardi (EPFL); Alberto Garcia-Duran (EPFL); Robert West (EPFL)<\/td><\/tr>
Collaborative Curating for Discovery and Expansion of Visual Clusters<\/td>Dung Duy Le (College of Engineering and Computer Science, VinUniversity)*; Hady Lauw (Singapore Management University)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#3 Web mining (IV)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
Cluster-Aware Heterogeneous Information Network Embedding<\/td>RayyanAhmad Khan (Technical University of Munich)*; Martin Kleinsteuber (Technical University of Munich)<\/td><\/tr>
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion<\/td>shijie zhang (The University of Queensland)*; Hongzhi Yin (The University of Queensland); Tong Chen (The University of Queensland); Zi Helen Huang (University of Queensland); Quoc Viet Hung Nguyen (Griffith University); Lizhen Cui (ShanDong University)<\/td><\/tr>
RecGURU: Adversarial Learning of Generalized User Representations for Cross-Domain Recommendation<\/td>Chenglin Li (University of Alberta)*; Mingjun Zhao (University of Alberta); huanming zhang (South China University of Technology); Chenyun YU (City University of Hong Kong); Lei Cheng (Tencent); Guoqiang Shu (Tencent); Jianming Yang (Tencent ); Di Niu (University of Alberta)<\/td><\/tr>
Personalized Transfer of User Preferences for Cross-domain Recommendation<\/td>Yongchun Zhu (Institute of Computing Technology, Chinese Academy of Sciences)*; Zhenwei Tang (King Abdullah University of Science and Technology); Yudan Liu (WeChat Search Application Department, Tencent); Fuzhen Zhuang (Institute of Artificial Intelligence, Beihang University); Ruobing Xie (WeChat Search Application Department, Tencent); Xu Zhang (WeChat Search Application Department, Tencent); Leyu Lin (WeChat Search Application Department, Tencent); Qing He (Institute of Computing Technology, Chinese Academy of Sciences)<\/td><\/tr>
A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion<\/td>Jianhuan Zhuo (Institute of Information Engineering, Chinese Academy of Sciences)*; Qiannan Zhu (Gaoling School of Artificial Intelligence, Renmin University of China); Yinliang Yue (Institute of Information Engineering, Chinese Academy of Sciences); Yuhong Zhao (Institute of Information Engineering, Chinese Academy of Sciences); Weisi Han (Institute of Information Engineering, Chinese Academy of Sciences)<\/td><\/tr>
Scope-aware Re-ranking with Gated Attention in Feed<\/td>Hao Qian (Ant Services Group)*; Qintong Wu (Ant Group ); Kai Zhang (University of Science and Technology of China); Zhiqiang Zhang (Ant Group); Lihong Gu (Ant Group); Xiaodong Zeng (Ant Services Group ); Jun Zhou (Ant Financial); Jinjie Gu (Ant Group)<\/td><\/tr>
Knowledge Enhanced Sports Game Summarization<\/td>Jiaan Wang (Soochow University)*; Zhixu Li (Fudan University); Tingyi Zhang (Soochow University); Duo Zheng (Beijing University of Posts and Telecommunications); JIanfeng Qu (Soochow University); An Liu (Soochow University); Lei Zhao (Soochow University); Zhigang Chen (iFLYTEK CO., LTD)<\/td><\/tr>
A Simple but Effective Bidirectional Framework for Relational Triple Extraction<\/td>Feiliang Ren (Northeastern University)*; Longhui Zhang (Northeastern University); Shujuan Yin (Northeastern University); Xiaofeng Zhao (Northeastern University); Shilei Liu (Northeastern University); Bochao Li (Northeastern University)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#4 Social Networks \/ Web mining (II)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
MTLVS: A Multi-Task Framework to Verify and Summarize Crisis-Related Microblogs<\/td>Rajdeep Mukherjee (IIT Kharagpur)*; Uppada Vishnu (IIT Kharagpur); Chandana Peruri (IIT Kharagpur); Sourangshu Bhattacharya (IIT KHARAGPUR); niloy ganguly (IIT Kharagpur); Pawan Goyal ( Indian Institute of Technology Kharagpur); Koustav Rudra (Leibniz Universit\u00e4t Hannover)<\/td><\/tr>
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs<\/td>Hyeonjeong Shin (KAIST); Taehyung Kwon (KAIST); Neil Shah (Snap Inc.); Kijung Shin (KAIST)*<\/td><\/tr>
Ranking Friend Stories on Social Platforms with Edge-Contextual Local Graph Convolutions<\/td>Xianfeng Tang (Amazon)*; Yozen Liu (Snap Inc); Xinran He (Snap Inc.); Suhang Wang (Pennsylvania State University); Neil Shah (Snap Inc.)<\/td><\/tr>
Geometric Inductive Matrix Completion: A Hyperbolic Approach with Unified Message Passing<\/td>Chengkun Zhang (the University of Sydney)*; Hongxu Chen (University of Technology Sydney); Sixiao Zhang (University of Technology Sydney); Guandong Xu (University of Technology Sydney, Australia); Junbin Gao (University of Sydney, Australia)<\/td><\/tr>
Graph Few-shot Class-incremental Learning<\/td>Zhen Tan (Arizona State University)*; Kaize Ding (Arizona State University); Ruocheng Guo (City University of Hong Kong); Huan Liu (Arizona State University)<\/td><\/tr>
Identifying Cost-effective Debunkers for Multi-stage Fake News Mitigation Campaigns<\/td>Xiaofei Xu (RMIT University)*; KE DENG (RMIT University); Xiuzhen Zhang (RMIT University)<\/td><\/tr>
A Counterfactual Modeling Framework for Churn Prediction<\/td>Guozhen Zhang (Tsinghua University)*; Jinwei Zeng (Tsinghua University); Zhengyue Zhao (Tsinghua University); Depeng Jin (Tsinghua University); Yong Li (Tsinghua University)<\/td><\/tr>
Directed Network Embedding with Virtual Negative Edges<\/td>Hyunsik Yoo (Hanyang University); Yeon-Chang Lee (Hanyang University); Kijung Shin (KAIST); Sang-Wook Kim (Hanyang University, Korea)*<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#5 Intelligent Assistant (I)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources<\/td>Sixing Wu (Peking University)*; Minghui Wang (Peking University); Ying Li (Peking University); Dawei Zhang (Peking University); Zhonghai Wu (Peking University)<\/td><\/tr>
Unsupervised Cross-Domain Adaptation for Response Selection Using Self-Supervised and Adversarial Training<\/td>Jia Li (Peking University); Chongyang Tao (Microsoft)*; Huang Hu (Microsoft); Can Xu (microsoft); Yining Chen (Microsoft); Daxin Jiang (Microsoft, Beijing, China)<\/td><\/tr>
On Sampling Collaborative Filtering Datasets<\/td>Noveen Sachdeva (UC San Diego)*; Carole-Jean Wu (Facebook AI Research); Julian McAuley (UCSD)<\/td><\/tr>
Choosing the Best of All Worlds: Accurate, Diverse, and Novel Recommendations through Multi-Objective Reinforcement Learning<\/td>Du\u0161an Stamenkovi\u0107 (Department of Mathematics and Informatics, University of Novi Sad)*; Alexandros Karatzoglou (Google Research); Ioannis Arapakis (Telefonica Research); Xin Xin (Shandong University); Kleomenis Katevas (Telefonica Research)<\/td><\/tr>
Deep-QPP: A Pairwise Interaction-based Deep Learning Model for Supervised Query Performance Prediction<\/td>Suchana Datta (University College Dublin)*; Debasis Ganguly (University of Glasgow); Derek Greene (University College Dublin); Mandar Mitra (Indian Statistical Institute, Kolkata)<\/td><\/tr>
Supervised Advantage Actor-Critic for Recommender Systems<\/td>Xin Xin (Shandong University); Alexandros Karatzoglou (Google Research)*; Ioannis Arapakis (Telefonica Research); Joemon M Jose ( University of Glasgow)<\/td><\/tr>
Learning Relevant Questions for Conversational Product Search using Reinforcement Learning<\/td>Ali Montazeralghaem (University of Massachusetts Amherst)*; James Allan (University of Massachusetts Amherst)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#6 Privacy (I)<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
Learning Fair Node Representations with Graph Counterfactual Fairness<\/td>Jing Ma (University of Virginia)*; Ruocheng Guo (City University of Hong Kong); Mengting Wan (Microsoft); Longqi Yang (Microsoft); Aidong Zhang (University of Virginia); Jundong Li (University of Virginia)<\/td><\/tr>
Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning<\/td>Yingqiang Ge (Rutgers University)*; Xiaoting Zhao (Etsy); Lucia Yu (Etsy); Saurabh Paul (Etsy); Diane Hu (Etsy); Yongfeng Zhang (Rutgers University)<\/td><\/tr>
Towards Fair Classifiers Without Sensitive Attributes: ExploringBiases in Related Features<\/td>Tianxiang Zhao (Penn State University)*; Enyan Dai (The Pennsylvania State University); Kai Shu (Illinois Institute of Technology); Suhang Wang (Pennsylvania State University)<\/td><\/tr>
Understanding and Mitigating the Effect of Outliers in Fair Ranking<\/td>Fatemeh Sarvi (University of Amsterdam)*; Maria Heuss (University of Amsterdam); Mohammad Aliannejadi (University of Amsterdam); Sebastian Schelter (University of Amsterdam); Maarten de Rijke (University of Amsterdam & Ahold Delhaize)<\/td><\/tr>
Introducing the Expohedron for efficient Pareto-optimal fairness-utility amortizations in repeated rankings<\/td>Till Kletti (NaverLabs Europe)*; Jean-Michel Renders (NAVER LABS Europe); Patrick Loiseau (Inria)<\/td><\/tr>
Assessing Algorithmic Biases for Musical Version Identification<\/td>Furkan Yesiler (Universitat Pompeu Fabra)*; Marius Miron (Universitat Pompeu Fabra); Joan Serra (Dolby Laboratories); Emilia Gomez (Universitat Pompeu Fabra)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

#7 Web of Things \/ Crowdsourcing<\/strong><\/p>\n\n\n\n

Paper Title<\/strong><\/td>Authors<\/strong><\/td><\/tr>
Keyword Assisted Embedded Topic Model<\/td>Bahareh Harandizadeh (University of Southern California)*; J. Hunter Priniski (University of California, Los Angeles); Fred Morstatter (University of Southern California)<\/td><\/tr>
Combinatorial Bandits under Strategic Manipulations<\/td>Jing Dong (The Chinese University of Hong Kong, Shenzhen)*; Ke Li (The Chinese University of Hong Kong, Shenzhen); Shuai Li (Shanghai Jiao Tong University); Baoxiang Wang (The Chinese University of Hong Kong, Shenzhen)<\/td><\/tr>
Crowdsourcing-based Multi-Device Communication Cooperation for Mobile High-Quality Video Enhancement<\/td>Xiaotong Wu (Nanjing Normal University)*; Lianyong Qi (Qufu Normal University); Xiaolong Xv (Nanjing University of Information Science and Technology); Shui Yu (University of Technology Sydney (UTS)); Wanchun Dou (Nanjing University); Xuyun Zhang (Macquarie University)<\/td><\/tr>
ST-GSP: Spatial-Temporal Global Semantic Representation Learning for Urban Flow Prediction<\/td>Liang Zhao (Chongqing University); Min Gao (Chongqing University)*; Zongwei Wang (Chongqing University)<\/td><\/tr>
VAE++: Variational AutoEncoder for Heterogeneous One-Class Collaborative Filtering<\/td>Wanqi Ma (Shenzhen University); Xiancong Chen (Shenzhen University); Weike Pan (Shenzhen University)*; Zhong Ming (Shenzhen University)<\/td><\/tr>
Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction<\/td>Jinquan Hang (Peking University)*; Zheng Dong (Baidu); Hengshu Zhu (Baidu); Hongke Zhao (Tianjin University); Xin Song (Baidu Inc.); Peng Wang (Baidu Inc.)<\/td><\/tr>
PLdFe-RR:Personalized Long-distance Fuel-efficient Route Recommendation Based On Historical Trajectory<\/td>Zhan Wang (Shandong University); Zhaohui Peng (Shandong University)*; Senzhang Wang (Central South University); Qiao Song (Shandong University)<\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

#1 Web mining \/ Web Search (III) Paper Title Authors MAVE: A Product Dataset for Multi-source Attribute Value Extraction Li Yang (Google Research); Qifan Wang (Google Research)*; Zac Yu (Google); Anand Kulkarni (Google); Sumit Sanghai (Google LLC); Bin Shu (Google); Jonathan Elsas (Google); Bhargav Kanagal (Google) Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning … <\/p>\n","protected":false},"author":1,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","mp-event_category":[],"mp-event_tag":[],"class_list":["post-1219","mp-event","type-mp-event","status-publish","hentry","latest_post","mp-event-item"],"_links":{"self":[{"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/mp-event\/1219","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/mp-event"}],"about":[{"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/types\/mp-event"}],"author":[{"embeddable":true,"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/comments?post=1219"}],"wp:attachment":[{"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/media?parent=1219"}],"wp:term":[{"taxonomy":"mp-event_category","embeddable":true,"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/mp-event_category?post=1219"},{"taxonomy":"mp-event_tag","embeddable":true,"href":"http:\/\/www.wsdm-conference.org\/2022\/wp-json\/wp\/v2\/mp-event_tag?post=1219"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}