The following papers have been accepted at SIGIR eCom 2021:

Workshop Papers

   1  . A Deep Reinforcement Learning-Based Approach to Query-Free Interactive Target Item Retrieval  [PDF]
          Anna Sepliarskaia, Sahika Genc and Maarten de Rijke.
   2  . Conditional Sequential Slate Optimization  [PDF]
          Yipeng Zhang, Mingjian Lu, Saratchandra Indrakanti, Manojkumar Rangasamy Kannadasan and Abraham Bagherjeiran.
   3  . Tackling Attribute Fine-grainedness in Cross-modal Fashion Search with Multi-level Features  [PDF]
          Kenneth Goei, Mariya Hendriksen and Maarten de Rijke.
   4  . Preventing Contrast Effect Exploitation in Recommendations  [PDF]
          Chris Nota, Georgios Theocharous, Michele Saad and Philip S. Thomas.
   5  . Predicting Completeness of Unstructured Shipping Addresses Using Ensemble Models  [PDF]
          Vedang Anand Waradpande, Vinay Surya Prakash Petchetti, Nikhil Jhaveri and Shashank Agarwal.
   6  . Real-Time Personalized Ranking in E-commerce Search  [PDF]
          Lucia Yu, Ethan Benjamin, Xiaoting Zhao, Congzhe Su, Yinlin Fu, Jon Eskreis-Winkler and Diane Hu.
   7  . Featured Keywords: Enabling Product Discovery in E-Commerce Through Unstructured Product Attributes  [PDF]
          Janani Balaji, Venkata Simhadri, Suhail Shaikh, Olga Stolpovskaia and Jeyaprakash Singarayar.
   8  . Quotient Space-Based Keyword Retrieval in Sponsored Search  [PDF]
          Yijiang Lian, Shuang Li, Chaobing Feng and Yanfeng Zhu.
   9  . Neural Search: Learning Query and Product Representations in Fashion E-commerce  [PDF]
          Sagnik Sarkar and Lakshya Kumar.
   10. The Last Mile: Taking Query Language Identification from Model Ready to Production  [PDF]
          Tracy Holloway King, Chirag Arora, Francois Guerin, Sachin Kelkar and Judy Massuda.
   11. “Are you sure?”: Preliminary Insights from Scaling Product Comparisons to Multiple Shops  [PDF]
          Patrick John Chia, Bingqing Yu and Jacopo Tagliabue.
   12. Improving Cold-start Item Advertisement For Small Businesses  [PDF]
          Yang Shi and Young-joo Chung.
   13. DeepCAT: Deep Category Representation for Query Understanding in E-commerce Search  [PDF]
          Ali Ahmadvand, Surya Kallumadi, Faizan Javed and Eugene Agichtein.
   14. Exploring Collaborative Navigation Support in Collaborative Product Search  [PDF]     
          Felipe Moraes, David Maxwell and Claudia Hauff.
   15. NeuralNDCG: Direct Optimisation of a Ranking Metric via Differentiable Relaxation of Sorting  [PDF]
          Przemysław Pobrotyn and Radosław Białobrzeski.
   16. Aligning Hotel Embeddings using Domain Adaptation for Next-Item Recommendation  [PDF]
          Ioannis Partalas.
   17. Evaluation of Multi-Field Models in Neural Recipe Retrieval for Search  [PDF]
          Kentaro Takiguchi, Mikhail Fain, Niall Twomey and Luis Vaquero.

Data Challenge Papers

   1  . Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation  [PDF]
          Gabriel Moreira, Sara Rabhi, Ronay Ak, Md Yasin Kabir and Even Oldridge.
   2  . Comparison of Transformer-Based Sequential Product Recommendation Models for the Coveo Data Challenge  [PDF]
          Elisabeth Fischer, Daniel Zoller and Andreas Hotho.
   3  . Utilizing Graph Neural Network to Predict Next Items in Large-sized Session-based Recommendation Industry Data  [PDF]
          Tianqi Wang, Zhongfen Deng, Houwei Chou, Lei Chen and Wei-Te Chen.
   4  . Session-based Recommender System Using an Ensemble of Multiple NN Models with LSTM and Matrix Factorization  [PDF]
          Yoshihiro Sakatani.
   5  . Adversarial Validation to Select Validation Data for Evaluating Performance in E‑commerce Purchase Intent Prediction  [PDF]
          Shotaro Ishihara, Shuhei Goda and Hidehisa Arai.
   6  . A Session-aware DeepWalk Model for Session-based Recommendation  [PDF]
          Kaiyuan Li, Pengfei Wang and Long Xia.