The following papers have been accepted at SIGIR eCom 2022:

Workshop Papers
       1  . From Theory to Practice: Testing Harvesting-Based Propensity Estimators on Counterfactual Learning-To-Rank from Implicit Feedback for E-commerce Search  [PDF]
              Parantapa Goswami, Andrés Hoyos-Idrobo, Théo Deschamps and Nicolas Feuillet.
       2  . ShopTalk: A System for Conversational Faceted Search  [PDF]
              Gurmeet Manku, James Lee-Thorp, Bhargav Kanagal, Joshua Ainslie, Jingchen Feng, Zach Pearson, Ebenezer Anjorin,
              Sudeep Gandhe, Ilya Eckstein, Jim Rosswog, Sumit Sanghai, Michael Pohl, Larry Adams and D Sivakumar.
       3  . Simultaneously Improving Utility and User Experience in Task-oriented Dialogue Systems  [PDF]
              Phillip Lippe, Pengjie Ren, Hinda Haned, Bart Voorn and Maarten de Rijke.
       4  . Advancing Query Rewriting in E-Commerce via Shopping Intent Learning  [PDF]
              Mengxiao Zhang, Yongning Wu, Raif Rustamov, Hongyu Zhu, Haoran Shi, Yuqi Wu, Lei Tang, Zuohua Zhang and Chu Wang.
       5  . Learning to Ask Critical Questions for Assisting Product Search  [PDF]
              Zixuan Li, Lizi Liao and Tat-Seng Chua.
       6  . Study of Encoder-Decoder Architectures for Code-Mix Search Query Translation  [PDF]
              Mandar Kulkarni, Soumya Chennabasavaraj and Nikesh Garera.
       7  . Trends-enhanced Attention & Memory Networks for E-commerce Recommendation  [PDF]
              Zhi Li, Daichi Amagata, Takuya Maekawa, Kei Yonekawa, Mori Kurokawa and Takahiro Hara.
       8  . Synthesized Corpora for Tagging Japanese Product Attribute Values in Low-resource Settings  [PDF]
              Yuki Nakayama, Koji Murakami, Erick Mendieta and Chen Zhao.
       9  . Block-SCL: Blocking Matters for Supervised Contrastive Learning in Product Matching  [PDF]
              Mario Almagro, David Jiménez-Cabello, Diego Ortego, Emilio Almazán and Eva Martínez García.
       10. HISS: A Novel Hybrid Inference Architecture in Embedding Based Product Sourcing using Knowledge Distillation  [PDF]
                Ankith M S, Sourab Mangrulkar and Vivek Sembium.
       11. UNDR: User-Needs-Driven Ranking of Products in E-Commerce  [PDF]
                Andrea Papenmeier, Daniel Hienert, Firas Sabbah, Norbert Fuhr and Dagmar Kern.
       12. ListBERT: Learning to Rank E-commerce products with Listwise BERT  [PDF]
                Lakshya Kumar and Sagnik Sarkar.
       13. When Volatility Reigns: Learning to Rank Recommendations in Second Hand Marketplaces  [PDF]
                Jose San Pedro, Jordi Esteve, Victor Codina and Sandra García.
       14. Vernacular Search Query Translation with Unsupervised Domain Adaptation  [PDF]
                Mandar Kulkarni and Nikesh Garera.
       15. Fire Dragon and Unicorn Princess Gender Stereotypes and Children’s Products in Search Engine Responses  [PDF]
                Amifa Raj and Michael Ekstrand.
       16. Incorporating Customer Reviews in Size and Fit Recommendation systems for Fashion E-Commerce  [PDF]
                Oishik Chatterjee, Jaidam Ram Tej and Narendra Varma Dasararaju.
       17. Product Review Image Ranking for Fashion E-commerce  [PDF]
                Sangeet Jaiswal, Dhruv Patel, Sreekanth Vempati and Konduru Saiswaroop.
       18. Contrastive Learning for Interactive Recommendation in Fashion  [PDF]
                Karin Sevegnani, Arjun Seshadri, Tian Wang, Anurag Beniwal, Julian McAuley, Alan Lu and Gerard Medioni.
       19. An Embedding-Based Grocery Search Model at Instacart  [PDF]
                Yuqing Xie, Taesik Na, Xiao Xiao, Saurav Manchanda, Young Rao, Zhihong Xu, Guanghua Shu, Esther Vasiete, Tejaswi Tenneti and Haixun Wang.
       20. Multi-objective ranking with directions of preferences  [PDF]
                Michinari Momma, Chaosheng Dong and Yetian Chen.
       21. Rule-Guided Knowledge-Graph based Negative Sampling for Outfit Recommendation  [PDF]
                Huijing Zhan, Ling Li, Xue Geng, Jie Lin and Alex Kot.
       22. PSimBERT: Query Phrase Expansion for Low Recall Vocabulary Gap Queries  [PDF]
                Rohan Kumar, Surender Kumar and Samir Shah.

Data Challenge Papers
       1  . Two-Stage Approach for Predicting Fashion Compatibility  [PDF]
              Adilzhan Ismailov.
       2  . Outfit Recommendation Based on Collaborative Filtering  [PDF]
              Selman Delil, Birol Kuyumcu.