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.