Challenges and research opportunities in eCommerce search and recommendations
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M. de Rijke | Tracy Holloway King | Manos Tsagkias | Vanessa Murdock | Maarten de Rijke | Surya Kallumadi | S. Kallumadi | Vanessa Murdock | M. Tsagkias
[1] Jamie Callan,et al. Deeper Text Understanding for IR with Contextual Neural Language Modeling , 2019, SIGIR.
[2] Mark Sanderson,et al. How Do People Interact in Conversational Speech-Only Search Tasks: A Preliminary Analysis , 2017, CHIIR.
[3] Yujing Hu,et al. Reinforcement Learning to Rank in E-Commerce Search Engine: Formalization, Analysis, and Application , 2018, KDD.
[4] Matthew Pearson,et al. Bias and Reciprocity in Online Reviews: Evidence From Field Experiments on Airbnb , 2015, EC.
[5] Fernando Diaz,et al. Towards a Fair Marketplace: Counterfactual Evaluation of the trade-off between Relevance, Fairness & Satisfaction in Recommendation Systems , 2018, CIKM.
[6] Thomas Blake,et al. Returns to Consumer Search: Evidence from eBay , 2016, EC.
[7] Yiqun Liu,et al. User Intent, Behaviour, and Perceived Satisfaction in Product Search , 2018, WSDM.
[8] Xiao Li,et al. Learning query intent from regularized click graphs , 2008, SIGIR '08.
[9] Krisztian Balog,et al. Head First: Living Labs for Ad-hoc Search Evaluation , 2014, CIKM.
[10] Steven Tadelis. Two-sided e-commerce marketplaces and the future of retailing , 2016 .
[11] Beste F. Yuksel,et al. Brains or Beauty , 2017, ACM Trans. Internet Techn..
[12] Jie Yang,et al. The Role of Attributes in Product Quality Comparisons , 2020, CHIIR.
[13] Milad Shokouhi,et al. Behavioral dynamics on the web: Learning, modeling, and prediction , 2013, TOIS.
[14] Andrei Broder,et al. A taxonomy of web search , 2002, SIGF.
[15] W. Bruce Croft,et al. User Intent Prediction in Information-seeking Conversations , 2019, CHIIR.
[16] Ricardo Baeza-Yates. Semantic Query Understanding , 2017, SIGIR '17.
[17] Elad Haramaty,et al. Why Do People Buy Seemingly Irrelevant Items in Voice Product Search?: On the Relation between Product Relevance and Customer Satisfaction in eCommerce , 2020, WSDM.
[18] Craig MacDonald,et al. Exploiting query reformulations for web search result diversification , 2010, WWW '10.
[19] Iadh Ounis,et al. FACTS-IR: Fairness, Accountability, Confidentiality, Transparency, and Safety in Information Retrieval , 2019 .
[20] M. de Rijke,et al. Improving Outfit Recommendation with Co-supervision of Fashion Generation , 2019, WWW.
[21] Mounia Lalmas,et al. Tutorial on Online User Engagement: Metrics and Optimization , 2019, WWW.
[22] Marilyn A. Walker,et al. Learning to Predict Problematic Situations in a Spoken Dialogue System: Experiments with How May I Help You? , 2000, ANLP.
[23] Mark Sanderson,et al. Extracting audio summaries to support effective spoken document search , 2017, J. Assoc. Inf. Sci. Technol..
[24] Andrew Trotman,et al. The Architecture of eBay Search , 2017, eCOM@SIGIR.
[25] Maxine Eskénazi,et al. Let's go public! taking a spoken dialog system to the real world , 2005, INTERSPEECH.
[26] Tefko Saracevic,et al. RELEVANCE: A review of and a framework for the thinking on the notion in information science , 1997, J. Am. Soc. Inf. Sci..
[27] Filip Radlinski,et al. Towards Conversational Recommender Systems , 2016, KDD.
[28] Oren Kurland,et al. Query Expansion Using Word Embeddings , 2016, CIKM.
[29] Shubhra Kanti Karmaker Santu,et al. On Application of Learning to Rank for E-Commerce Search , 2017, SIGIR.
[30] Maarten de Rijke,et al. OpenSearch: Lessons Learned from an Online Evaluation Campaign , 2018, ACM J. Data Inf. Qual..
[31] Paul N. Bennett,et al. Leading Conversational Search by Suggesting Useful Questions , 2020, WWW.
[32] Hinda Haned,et al. Actionable Interpretability through Optimizable Counterfactual Explanations for Tree Ensembles , 2019, ArXiv.
[33] Faizan Javed,et al. JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search , 2020, SIGIR.
[34] David Carmel,et al. Promoting Relevant Results in Time-Ranked Mail Search , 2017, WWW.
[35] Henriette Cramer,et al. Assessing and addressing algorithmic bias in practice , 2018, Interactions.
[36] M. de Rijke,et al. Do News Consumers Want Explanations for Personalized News Rankings , 2017 .
[37] Alex Pentland,et al. Fair, Transparent, and Accountable Algorithmic Decision-making Processes , 2017, Philosophy & Technology.
[38] Xiaofeng Meng,et al. Query Understanding through Knowledge-Based Conceptualization , 2015, IJCAI.
[39] S. Robertson. The probability ranking principle in IR , 1997 .
[40] Gilles Brassard,et al. Alambic: a privacy-preserving recommender system for electronic commerce , 2008, International Journal of Information Security.
[41] Maarten de Rijke,et al. News Comments: Exploring, Modeling, and Online Prediction , 2010, ECIR.
[42] Enhong Chen,et al. Context-aware query suggestion by mining click-through and session data , 2008, KDD.
[43] Krisztian Balog,et al. Extended Overview of the Living Labs for Information Retrieval Evaluation (LL4IR) CLEF Lab 2015 , 2015, CLEF.
[44] M. de Rijke,et al. To Model or to Intervene: A Comparison of Counterfactual and Online Learning to Rank from User Interactions , 2019, SIGIR.
[45] M. de Rijke,et al. A Survey of Query Auto Completion in Information Retrieval , 2016, Found. Trends Inf. Retr..
[46] Daria Sorokina,et al. Amazon Search: The Joy of Ranking Products , 2016, SIGIR.
[47] J. Rowley. Product search in e‐shopping: a review and research propositions , 2000 .
[48] Michael Chau,et al. The Impact of Query Suggestion in E-Commerce Websites , 2011, WEB.
[49] Elad Haramaty,et al. Multi-Objective Ranking Optimization for Product Search Using Stochastic Label Aggregation , 2020, WWW.
[50] Andrew Trotman,et al. Report on the SIGIR 2019 Workshop on eCommerce (ECOM19) , 2019, ArXiv.
[51] Mohit Sharma,et al. Mining E-Commerce Query Relations using Customer Interaction Networks , 2018, WWW.
[52] Paul Resnick,et al. Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system , 2002, The Economics of the Internet and E-commerce.
[53] M. de Rijke,et al. Learning Latent Vector Spaces for Product Search , 2016, CIKM.
[54] Paul N. Bennett,et al. Generating Clarifying Questions for Information Retrieval , 2020, WWW.
[55] Thorsten Joachims,et al. Fairness of Exposure in Rankings , 2018, KDD.
[56] Giuseppe Riccardi,et al. Automated Natural Spoken Dialog , 2002, Computer.
[57] Maarten de Rijke,et al. ViTOR: Learning to Rank Webpages Based on Visual Features , 2019, WWW.
[58] M. de Rijke,et al. Unbiased Learning to Rank: Counterfactual and Online Approaches , 2019, WWW.
[59] David Lazer,et al. Auditing Autocomplete: Suggestion Networks and Recursive Algorithm Interrogation , 2019, WebSci.
[60] Brian D. Davison,et al. Learning to rank for freshness and relevance , 2011, SIGIR.
[61] Dominik Kowald,et al. The Unfairness of Popularity Bias in Music Recommendation: A Reproducibility Study , 2019, ECIR.
[62] Bhaskar Mitra,et al. An Introduction to Neural Information Retrieval , 2018, Found. Trends Inf. Retr..
[63] Mohit Sharma,et al. A Taxonomy of Queries for E-commerce Search , 2018, SIGIR.