Schedule

• Training Effective Neural CLIR by Bridging the Translation Gap. Hamed Bonab, Sheikh Muhammad Sarwar, and James Allan
• A Quantum Interference Inspired Neural Matching Model for Ad-hoc Retrieval. Yongyu Jiang, Peng Zhang, Hui Gao, and Dawei Song
• A Deep Recurrent Survival Model for Unbiased Ranking. Jiarui Jin, Yuchen Fang, Weinan Zhang, Kan Ren, Guorui Zhou, Jian Xu, Yong Yu, Jun Wang, Xiaoqiang Zhu, and Kun Gai
• ColBERT: Efficient and Effective Search via Contextualized Late Interaction over BERT. Omar Khattab and Matei Zaharia
• Efficient Document Re-Ranking for Transformers by Precomputing Term Representations. Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, Ophir Frieder
• A Reinforcement Learning Framework for Relevance Feedback, Ali Montazeralghaem, Hamed Zamani, and James Allan

• Fairness-Aware Explainable Recommendation over Knowledge Graphs. Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, and Gerard de Melo
• Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. Jibing Gong, Shen Wang, Jinlong Wang, Hao Peng, Wenzheng Feng, Dan Wang, Yi Zhao, Huanhuan Li, Jie Tang, and P. Yu
• Sequential Recommendation with Self-attentive Multi-adversarial Network. Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, and Ji-Rong Wen
• MVIN: Learning multiview items for recommendation. Chang-You Tai, Meng-Ru Wu, Yun-Wei Chu, Shao-Yu Chu, and Lun-Wei Ku
• Make It a CHORUS: Context- and Knowledge-aware Item Modeling for Recommendation. Chenyang Wang, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma
• Evolutionary Product Description Generation: A Dynamic Fine-Tuning Approach Leveraging User Click Behavior. Yongzhen Wang, Jian Wang, Heng Huang, Hongsong Li, and Xiaozhong Liu

• Pairwise View Weighted Graph Network for View-based 3D Model Retrieval. Zan Gao, Yin-Ming Li, Wei-Li Guan, Wei-Zhi Nie, Zhi-Yong Cheng, and An-An Liu
• Detecting User Community in Sparse Domain via Cross-Graph Pairwise Learning. Zheng Gao, Hongsong Li, Zhuoren Jiang, and Xiaozhong Liu
• BiANE: Bipartite Attributed Network Embedding. Wentao Huang, Yuchen Li, Yuan Fang, Ju Fan, and Hongxia Yang
• Hierarchical Fashion Graph Network for Personalised Outfit Recommendation. Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao, and Tat-Seng Chua
• Global Context Enhanced Graph Nerual Networks for Session-based Recommendation. Ziyang Wang, Wei Wei, Cong Gao, Xiaoli Li, Xianling Mao, and Minghui Qiu
• Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning. Sijin Zhou, Xinyi Dai, Haokun Chen, Weinan Zhang, Kan Ren, Ruiming Tang, Xiuqiang He, and Yong Yu

• Invited talk: Large-scale Multi-modal Search and QA at Alibaba. Rong Jin
• User Behavior Retrieval for Click-Through Rate Prediction. Jiarui Qin, Weinan Zhang, Xin Wu, Jiarui Jin, Yuchen Fang, and Yong Yu
• How Airbnb Tells You Will Enjoy Sunset Sailing in Barcelona? Recommendation in a Two-Sided Travel Marketplace. Liang Wu and Mihajlo Grbovic

• Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation. Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma
• AutoGroup: Automatic Feature Grouping for Modelling Explicit High-Order Feature Interactions in CTR Prediction. Bin Liu, Niannan Xue, Huifeng Guo, Ruiming Tang, Stefanos Zafeiriou, Xiuqiang He, and Zhenguo Li
• KERL: A Knowledge-Guided Reinforcement Learning Model for Sequential Recommendation. Pengfei Wang, Yu Fan, Long Xia, Wayne Xin Zhao, Shaozhang Niu, and Jimmy Huang
• CKAN: Collaborative Knowledge-aware Attentive Network for Recommender Systems. Ze Wang, Lin Guangyan, Huobin Tan, Qinghong Chen, and Xiyang Liu
• CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network. Cheng Zhao, Chenliang Li, Rong Xiao, Hongbo Deng, and Aixin Sun
• Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs. Kangzhi Zhao, Xiting Wang, Yuren Zhang, Li Zhao, Zheng Liu, Chunxiao Xing, and Xing Xie
• Incorporating Scenario Knowledge into A Unified Fine-tuning Architecture for Event Representation. Jianming Zheng, Fei Cai, and Honghui Chen

• Ranking-Incentivized Quality Preserving Content Modification. Gregory Goren, Oren Kurland, Moshe Tennenholtz, and Fiana Raiber
• On Understanding Data Worker Interaction Behaviors. Lei Han, Tianwa Chen, Gianluca Demartini, Marta Indulska, and Shazia Sadiq
• Creating a Children-Friendly Reading Environment via Joint Learning of Content and Human Attention. Guoxiu He, Yangyang Kang, Zhuoren Jiang, Jiawei Liu, Changlong Sun, Xiaozhong Liu, and Wei Lu
• Octopus: Comprehensive and Elastic User Representation for the Generation of Recommendation Candidates. Zheng Liu, Junhan Yang, Jianxun Lian, Defu Lian, and Xing Xie
• The Cortical Activity of Graded Relevance. Zuzana Pinkosova, William McGeown, and Yashar Moshfeghi
• Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback. Yuta Saito
• Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation. Shaoyun Shi, Weizhi Ma, Min Zhang, Yongfeng Zhang, Xinxing Yu, Houzhi Shan, Yiqun Liu, and Shaoping Ma

• Measuring Recommendation Explanation Quality: The Conflicting Goals of Explanations. Krisztian Balog and Filip Radlinski
• Bayesian Inferential Risk Evaluation on Multiple IR Systems. Rodger Benham, Ben Carterette, J. Shane Culpepper, and Alistair Moffat
• How to Measure the Reproducibility of System-oriented IR Experiments. Timo Breuer, Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Philipp Schaer, and Ian Soboroff
• Good Evaluation Measures based on Document Preferences. Tetsuya Sakai and Zhaohao Zeng
• Preference-based Evaluation Metrics for Web Image Search. Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Maarten de Rijke, Haitian Chen, Min Zhang, and Shaoping Ma
• Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics. Fan Zhang, Jiaxin Mao, Yiqun Liu, Xiaohui Xie, Weizhi Ma, Min Zhang, and Shaoping Ma
• Cascade or Recency: Constructing Better Evaluation Metrics for Session Search. Fan Zhang, Jiaxin Mao, Yiqun Liu, Weizhi Ma, Min Zhang, and Shaoping Ma

• Efficient and Effective Query Auto-Completion. Simon Gog, Giulio Ermanno Pibiri, and Rossano Venturini
• ATBRG: Adaptive Target-Behavior Relational Graph Network for Effective Recommendation. Yufei Feng, Binbin Hu, Fuyu Lv, Qingwen Liu, Zhiqiang Zhang, and Wenwu Ou
• Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network. Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Bo Zhang, and Liefeng Bo
• Entire Space Multi-Task Modeling via Post-Click Behavior Decomposition for Conversion Rate Prediction. Hong Wen, Jing Zhang, Yuan Wang, Fuyu Lv, Wentian Bao, Quan Lin, and Keping Yang
• Automated Embedding Size Search in Deep Recommender Systems. Haochen Liu, Xiangyu Zhao, Chong Wang, Xiaobing Liu, and Jiliang Tang

Virtual Discussion Rooms are available.

• Operationalizing the Legal Principle of Data Minimization for Personalization. Asia J. Biega, Peter Potash, Hal Daumé III, Fernando Diaz, and Michèle Finck
• Learning Personalized Risk Preferences for Recommendation. Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, and Yongfeng Zhang
• Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines. Yang Liu, Xianzhuo Xia, Liang Chen, Xiangnan He, Carl Yang, and Zibin Zheng
• Controlling Fairness and Bias in Dynamic Ranking. Marco Morik, Ashudeep Singh, Jessica Hong, and Thorsten Joachims
• Can the Crowd Identify Misinformation Objectively? The Effects of Judgments Scale and Assessor's Bias. Kevin Roitero, Michael Soprano, Shaoyang Fan, Damiano Spina, Stefano Mizzaro, and Gianluca Demartini
• Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. Ziwei Zhu, Jianling Wang, and James Caverlee

• What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way. Erik Faessler, Michel Oleynik, and Udo Hahn
• Accelerated Convergence for Counterfactual Learning to Rank. Rolf Jagerman and Maarten de Rijke
• DVGAN: A Minimax Game for Search Result Diversification Combining Explicit and Implicit Features. Jiongnan Liu, Zhicheng Dou, Xiaojie Wang, Shuqi Lu, and Ji-Rong Wen
• Policy-Aware Unbiased Learning to Rank for Top-k Rankings. Harrie Oosterhuis and Maarten de Rijke
• SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval. Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, and Ji-Rong Wen
• Reinforcement Learning to Rank with Pairwise Policy Gradient. Jun Xu, Zeng Wei, Long Xia, Yanyan Lan, Dawei Yin, Xueqi Cheng, and Ji-Rong Wen

• Humor Detection in Product Question Answering Systems. Elad Kravi, David Carmel, and Yftah Ziser
• Training Curricula for Open Domain Answer Re-Ranking. Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, and Ophir Frieder
• Open-Retrieval Conversational Question Answering. Chen Qu, Liu Yang, Cen Chen, Minghui Qiu, W. Bruce Croft, and Mohit Iyyer
• Learning to Ask Screening Questions for Job Postings. Baoxu Shi, Shan Li, Jaewon Yang, Mustafa Emre Kazdagli, and Qi He
• Match$^2$: A Matching over Matching Model for Similar Question Identification. Zizhen Wang, Yixing Fan, Jiafeng Guo, Liu Yang, Ruqing Zhang, Yanyan Lan, Xueqi Cheng, Hui Jiang, and Xiaozhao Wang
• Answer Ranking for Product-Related Questions via Multiple Semantic Relations Modeling. Wenxuan Zhang, Yang Deng, and Wai Lam

• ESAM: Discriminative Domain Adaptation with Non-Displayed Items to Improve Long-Tail Performance. Zhihong Chen, Rong Xiao, Chenliang Li, Gangfeng Ye, Haochuan Sun, and Hongbo Deng
• Table Search Using a Deep Contextualized Language Model. Zhiyu Chen, Mohamed Trabelsi, Jeff Heflin, Yinan Xu, and Brian Davison
• Convolutional Embedding for Edit Distance. Xinyan Dai, Xiao Yan, Kaiwen Zhou, Yuxuan Wang, Han Yang, and James Cheng
• ASiNE: Adversarial Signed Network Embedding. Yeon-Chang Lee, Nayoun Seo, Sang-Wook Kim, and Kyungsik Han
• Efficient Graph Query Processing over Geo-Distributed Datacenters. Ye Yuan, Delong Ma, Zhenyu Wen, Yuliang Ma, Guoren Wang, and Lei Chen
• Spatio-Temporal Dual Graph Attention Network for Query-POI Matching. Zixuan Yuan, Hao Liu, Yanchi Liu, Denghui Zhang, Fei Yi, Nengjun Zhu, and Hui Xiong

• LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang, and Meng Wang
• GAME: Learning Graphical and Attentive Multi-view Embeddings for Occasional Group Recommendation. Zhixiang He, Chi-Yin Chow, and Jia-Dong Zhang
• Multi-behavior Recommendation with Graph Convolution Networks. Bowen Jin, Chen Gao, Xiangnan He, Yong Li, and Depeng Jin
• GAG: Global Attributed Graph Neural Network for Streaming Session-based Recommendation. Ruihong Qiu, Hongzhi Yin, Zi Huang, and Tong Chen
• Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach. Le Wu, Yonghui Yang, Kun Zhang, Richang Hong, Yanjie Fu, and Meng Wang
• GCN-Based User Representation Learning for Unifying Robust Recommendation and Fraudster Identification. Shijie Zhang, Hongzhi Yin, Tong Chen, Nguyen Quoc Viet Hung, Zi Huang, and Lizhen Cui

• Using Phoneme Representations to Build Predictive Models Robust to ASR Errors. Simone Filice, Anjie Fang, Nut Limsopatham, and Oleg Rokhlenko
• Knowledge Enhanced Personalized Search. Shuqi Lu, Zhicheng Dou, Chenyan Xiong, Xiaojie Wang, and Ji-Rong Wen
• Learning Dynamic Node Representations with Graph Neural Networks. Yao Ma, Ziyi Guo, Zhaochun Ren, Jiliang Tang, and Dawei Yin
• An Eye Tracking Study of Web Search by People with and without Dyslexia. Srishti Palani, Adam Fourney, Shane Williams, Kevin Larson, Irina Spiridonova, and Meredith Ringel Morris
• DGL-KE: Training knowledge graph embeddings at scale. Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Hao Xiong, Zheng Zhang, and George Karypis
• Neural Interactive Collaborative Filtering. Lixin Zou, Long Xia, Yulong Gu, Weidong Liu, Dawei Yin, Jimmy Huang, and Xiangyu Zhao

• Invited talk: The New TREC Track on Podcast Search and Summarization. Rosie Jones
• Think Beyond the Word: Understanding the Implied Textual Meaning by Digesting Context, Local, and Noise. Guoxiu He, Zhe Gao, Zhuoren Jiang, Yangyang Kang, Changlong Sun, Xiaozhong Liu, and Wei Lu
• Robust Layout-aware IE for Visually Rich Documents with Pre-trained Language Models. Mengxi Wei, Yifan He, and Qiong Zhang

• Fashion Compatibility Modeling through a Multi-modal Try-on-guided Scheme. Xue Dong, Jianlong Wu, Xuemeng Song, Hongjun Dai, and Liqiang Nie
• Spatial Object Recommendation with Hints: When Spatial Granularity Matters. Hui Luo, Jingbo Zhou, Zhifeng Bao, Shuangli Li, J. Shane Culpepper, Haochao Ying, Hao Liu, and Hui Xiong
• Product Bundle Identification using Semi-Supervised Learning. Hen Tzaban, Ido Guy, Asnat Greenstein-Messica, Arnon Dagan, Lior Rokach, and Bracha Shapira
• Coding Electronic Health Records with Adversarial Reinforcement Path Generation. Shanshan Wang, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Jian-Yun Nie, Jun Ma, and Maarten de Rijke
• Degree-Aware Alignment for Entities in Tail. Weixin Zeng, Xiang Zhao, Wei Wang, Jiuyang Tang, and Zhen Tan
• Regional Relation Modeling for Visual Place Recognition. Yingying Zhu, Biao Li, Jiong Wang, and Zhou Zhao

• A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data. Dugang Liu, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Weike Pan, and Zhong Ming
• Agreement and Disagreement between True and False-Positive Metrics in Recommender Systems Evaluation. Elisa Mena-Maldonado, Rocío Cañamares, Pablo Castells, Yongli Ren, and Mark Sanderson
• Leveraging Social Media for Medical Text Simplification. Nikhil Pattisapu, Nishant Prabhu, Smriti Bhati, and Vasudeva Varma
• Sampler Design for Implicit Feedback Data by Noisy-label Robust Learning. Wenhui Yu and Zheng Qin
• MaHRL: Multi-goals Abstraction based Deep Hierarchical Reinforcement Learning for Recommendations. Dongyang Zhao, Liang Zhang, Bo Zhang, Lizhou Zheng, Yongjun Bao, and Weipeng Yan
• Towards Question-based Recommender Systems. Jie Zou, Yifan Chen, and Evangelos Kanoulas

• Try This Instead: Personalized and Interpretable Substitute Recommendation. Tong Chen, Hongzhi Yin, Guanhua Ye, Zi Huang, Yang Wang, and Meng Wang
• Towards Linking Camouflaged Descriptions to Implicit Products in E-commerce. Longtao Huang, Bo Yuan, Rong Zhang, and Quan Lu
• Distributed Equivalent Substitution Training for Large-Scale Recommender Systems. Haidong Rong, Yangzihao Wang, Feihu Zhou, Junjie Zhai, Haiyang Wu, Rui Lan, Fan Li, Han Zhang, Yuekui Yang, Zhenyu Guo, and Di Wang
• Query Resolution for Conversational Search with Limited Supervision. Nikos Voskarides, Dan Li, Pengjie Ren, Evangelos Kanoulas, and Maarten de Rijke
• Self-Supervised Reinforcement Learning for Recommender Systems. Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, and Joemon Jose
• Generative Attribute Manipulation Scheme for Flexible Fashion Search. Xin Yang, Xuemeng Song, Xianjing Han, Haokun Wen, Jie Nie, and Liqiang Nie

• Understanding Echo Chambers in E-commerce Recommender Systems. Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, and Yongfeng Zhang
• Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning. Han Zhang, Songlin Wang, Kang Zhang, Zhiling Tang, Yunjiang Jiang, Yun Xiao, Paul Yan, and Wen-Yun Yang
• GMCM: Graph-based Micro-behavior Conversion Model for Post-click Conversion Rate Estimation. Wentian Bao, Hong Wen, Sha Li, Xiao-Yang Liu, Quan Lin, and Keping Yang
• A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Users. Ye Bi, Liqiang Song, Mengqiu Yao, Zhenyu Wu, Jianming Wang, and Jing Xiao
• Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, and Xiuqiang He

Virtual Discussion Rooms are available.

• How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models. Yashar Deldjoo, Tommaso Di Noia, Felice Antonio Merra, Eugenio Di Sciascio
• DPLCF: Differentially Private Local Collaborative Filtering. Chen Gao, Chao Huang, Dongsheng Lin, Yong Li, and Depeng Jin
• Content-aware Neural Hashing for Cold-start Recommendation. Casper Hansen, Christian Hansen, Jakob Grue Simonsen Stephen Alstrup, and Christina Lioma
• Meta Matrix Factorization for Federated Rating Predictions. Yujie Lin, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Dongxiao Yu, Jun Ma, Maarten de Rijke, and Xiuzhen Cheng
• The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation. Tobias Schnabel, Paul Bennett, Saleema Amershi, Peter Bailey, and Thorsten Joachims
• Disentangled Representations for Graph-based Collaborative Filtering. Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, and Tat-Seng Chua

• Domain-Adaptive Neural Automated Essay Scoring. Yue Cao, Hanqi Jin, Xiaojun Wan, and Zhiwei Yu
• ADORE: Aspect Dependent Online REview Labeling for Review Generation. Parisa Kaghazgaran, Jianling Wang, Ruihong Huang, and James Caverlee
• Finding the Best of Two Worlds: Faster and More Robust Top-k Document Retrieval. Omar Khattab, Mohammad Hammoud, and Tamer Elsayed
• Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste. Zahra Nazari, Christophe Charbuillet, Johan Pages, Martin Laurent, Denis Charrier, Briana Vecchione, and Benjamin Carterette
• Learning with Weak Supervision for Email Intent Detection. Kai Shu, Subhabrata Mukherjee, Guoqing Zheng, Ahmed Hassan Awadallah, Milad Shokouhi, and Susan Dumais
• 3D Self-Attention for Unsupervised Video Quantization. Jingkuan Song, Ruimin Lang, Xiaosu Zhu, Xing Xu, Lianli Gao, and Heng Tao Shen

• Modeling Personalized Item Frequency Information for Next-basket Recommendation. Haoji Hu, Xiangnan He, Jinyang Gao, and Zhi-Li Zhang
• Transfer Learning via Contextual Invariants for One-to-Many Cross-Domain Recommendation. Adit Krishnan, Mahashweta Das, Mangesh Bendre, Hao Yang, and Hari Sundaram
• Incorporating User Micro-behaviors and Item Knowledge into Multi-task Learning for Session-based Recommendation. Wenjing Meng, Deqing Yang, and Yanghua Xiao
• Next-item Recommendation with Sequential Hypergraphs. Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, and James Caverlee
• Encoding History with Context-aware Representation Learning for Personalized Search. Yujia Zhou, Zhicheng Dou, and Ji-Rong Wen
• Recommendation for New Users and New Items via Randomized Training and Mixture-of-Experts Transformation. Ziwei Zhu, Shahin Sefati, Parsa Saadatpanah, and James Caverlee

• Neural Representation Learning for Clarification in Conversational Search. Helia Hashemi, Hamed Zamani, and Bruce Croft
• Investigating Reference Dependence Effects on User Search Interaction and Satisfaction. Jiqun Liu and Fangyuan Han
• DukeNet: A Dual Knowledge Interaction Network for Knowledge-Grounded Conversation. Chuan Meng, Pengjie Ren, Zhumin Chen, Weiwei Sun, Zhaochun Ren, Zhaopeng Tu, and Maarten de Rijke
• What If Bots Feel Moods? Towards Controllable Retrieval-based Dialogue Systems with Emotion-Aware Transition Networks. Lisong Qiu, Ying Wai Shiu, Pingping Lin, Ruihua Song, Yue Liu, Dongyan Zhao, and Rui Yan
• Expressions of Style in Information Seeking Conversation with an Agent. Paul Thomas, Daniel Mcduff, Mary Czerwinski, and Nick Craswell
• Analyzing and Learning from User Interactions for Search Clarification. Hamed Zamani, Bhaskar Mitra, Everest Chen, Gord Lueck, Fernando Diaz, Paul Bennett, Nick Craswell, and Susan Dumais

• A Unified Dual-view Model for Review Summarization and Sentiment Classification with Inconsistency Loss. Hou Pong Chan, Wang Chen, and Irwin King
• Enhancing Text Classification via Discovering Additional Semantic Clues from Logograms. Chen Qian, Fuli Feng, Lijie Wen, Li Lin, and Tat-Seng Chua
• Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation. Le Wu, Yonghui Yang, Lei Chen, Defu Lian, Richang Hong, and Meng Wang
• Web-to-Voice Transfer for Product Recommendation on Voice. Rongting Zhang and Jie Yang
• Minimally Supervised Categorization of Text with Metadata. Yu Zhang, Yu Meng, Jiaxin Huang, Frank F. Xu, Xuan Wang, and Jiawei Han
• Joint Aspect-Sentiment Analysis with Minimal User Guidance. Honglei Zhuang, Fang Guo, Chao Zhang, Liyuan Liu, and Jiawei Han

• AR-CF: Augmenting Virtual Users and Items in Collaborative Filtering for Addressing Cold-Start Problems. Dong-Kyu Chae, Jihoo Kim, Sang-Wook Kim, and Duen Horng Chau
• Studying Product Competition Using Representation Learning. Fanglin Chen, Xiao Liu, Davide Proserpio, Isamar Troncoso, and Feiyu Xiong
• Deep Critiquing for VAE-based Recommender Systems. Kai Luo, Hojin Yang, Ga Wu, and Scott Sanner
• GroupIM: A Mutual Information Maximizing Framework for Neural Group Recommendation. Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei Zhang, Hao Yang, and Hari Sundaram
• Neighbor Interaction Aware Graph Convolution Networks for Recommendation. Jianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, and Mark Coates
• A General Network Compression Framework for Sequential Recommender Systems. Yang Sun, Fajie Yuan, Min Yang, Guoao Wei, Zhou Zhao, and Duo Liu

• A Counterfactual Framework for Seller-Side A/B Testing on Marketplaces. Viet Ha-Thuc, Avishek Dutta, Ren Mao, Matthew Wood, and Yunli Liu
• Knowledge Graph-based Event Embedding Framework for Financial Quantitative Investments. Dawei Cheng, Fangzhou Yang, Xiaoyang Wang, Ying Zhang, and Liqing Zhang
• FashionBERT: Text and Image Matching with Adaptive Loss for Cross-modal Retrieval. Dehong Gao, Linbo Jin, Ben Chen, Minghui Qiu, Yi Wei, Yi Hu, and Hao Wang
• Large Scale Abstractive Multi-Review Summarization (LSARS) via Aspect Alignment. Haojie Pan, Rongqin Yang, Xin Zhou, Rui Wang, Deng Cai, and Xiaozhong Liu
• Be Aware of the Hot Zone: A Warning System of Hazard Area Prediction to Intervene Novel Coronavirus COVID-19 Outbreak. Zhenxin Fu, Yu Wu, Hailei Zhang, Yichuan Hu, Dongyan Zhao, and Rui Yan

• Learning Efficient Representations of Mouse Movements toPredict User Attention in Sponsored Search. Ioannis Arapakis and Luis A. Leiva
• Query Reformulation in E-Commerce Search. Sharon Hirsch, Ido Guy, Alexander Nus, Arnon Dagan, and Oren Kurland
• Generating Images Instead of Retrieving them: Relevance feedback on Generative Adversarial Networks. Antti Ukkonen, Pyry Joona, and Tuukka Ruotsalo
• Tree-augmented Cross-Modal Encoding for Complex-Query Video Retrieval. Xun Yang, Jianfeng Dong, Yixin Cao, Xun Wang, Meng Wang, and Tat-Seng Chua
• Nonlinear Robust Discrete Hashing for Cross-Modal Retrieval. Zhan Yang, Jun Long, Lei Zhu, and Wenti Huang
• Employing Personal Word Embeddings for Personalized Search. Jing Yao, Zhicheng Dou, and Ji-Rong Wen

• Query Rewriting for Voice Shopping Null Queries. Iftah Gamzu, Marina Haikin, and Nissim Halabi
• Joint-modal Distribution-based Similarity Hashing for Large-scale Unsupervised Deep Cross-modal Retrieval. Song Liu, Shengsheng Qian, Yang Guan, Jiawei Zhan, and Long Ying
• Learning Colour Representations of Search Queries. Paridhi Maheshwari, Manoj Ghuhan A, and Vishwa Vinay
• Web Table Retrieval using Multimodal Deep Learning. Roee Shraga, Haggai Roitman, Guy Feigenblat, and Mustafa Canim
• Online Collective Matrix Factorization Hashing for Large-Scale Cross-Media Retrieval. Di Wang, Quan Wang, Yaqiang An, Xinbo Gao, and Yumin Tian
• Correlated Features Synthesis and Alignment for Zero-shot Cross-modal Retrieval. Xing Xu, Kaiyi Lin, Huimin Lu, Lianli Gao, and Heng Tao Shen

• HME: A Hyperbolic Metric Embedding Approach for Next-POI Recommendation. Shanshan Feng, Lucas Vinh Tran, Gao Cong, Lisi Chen, Jing Li, and Fan Li
• Dual Sequential Network for Temporal Sets Prediction. Leilei Sun, Yansong Bai, Bowen Du, Chuanren Liu, Hui Xiong, and Weifeng Lv
• Group-Aware Long- and Short-Term Graph Representation Learning for Sequential Group Recommendation. Wen Wang, Wei Zhang, Jun Rao, Zhijie Qiu, Bo Zhang, Leyu Lin, and Hongyuan Zha
• Time Matters: Sequential Recommendation with Complex Temporal Information. Wenwen Ye, Shuaiqiang Wang, Xu Chen, Xuepeng Wang, Zheng Qin, and Dawei Yin
• Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation. Fajie Yuan, Xiangnan He, Alexandros Karatzoglou, and Liguang Zhang
• How to Retrain a Recommender System? Yang Zhang, Xiangnan He, Fuli Feng, Chenxu Wang, Meng Wang, Yan Li, and Yongdong Zhang

• Network on Network for Tabular Data Classification in Real-world Applications, Yuanfei Luo, Hao Zhou, Weiwei Tu, Yuqiang Chen, Wenyuan Dai, and Qiang Yang
• Identifying Tasks from Mobile App Usage Patterns. Yuan Tian, Ke Zhou, Mounia Lalmas, and Dan Pelleg
• Efficient Image Gallery Representations at Scale through Multi-task Learning. Benjamin Gutelman and Pavel Levin