=Paper= {{Paper |id=Vol-2410/xpreface |storemode=property |title=None |pdfUrl=https://ceur-ws.org/Vol-2410/xpreface.pdf |volume=Vol-2410 }} ==None== https://ceur-ws.org/Vol-2410/xpreface.pdf
                                         Preface



   This proceedings contains the accepted papers of the SIGIR 2019 Workshop on eCommerce
(ECOM19), a full day workshop that took place on Thursday, July 25, 2019 in Paris, France. The
workshop was held in conjunction with SIGIR 2019. The purpose of the workshop was to serve
as a platform for publication and discussion of Information Retrieval and NLP research and their
applications in the domain of eCommerce.
   eCommerce Information Retrieval has received little attention in the academic literature, yet
it is an essential component of some of the largest web sites (such as eBay, Amazon, Airbnb,
Alibaba, Taobao, Target, The Home Depot, and others). The SIGIR 2019 Workshop on eCommerce
(ECOM19) brought together researchers and practitioners of eCommerce IR to discuss topics
unique to it, to set a research agenda going forward, and to examine how to build a data set for
research. Our primary motivation as organizers of this workshop was to create a community and
act as a forum to discuss interesting research ideas and challenges in the eCommerce domain.
   The workshop drew contributions from both industry as well as academia, in total the workshop
received thirty nine submissions, and accepted twenty four papers (62%). The submissions were
reviewed by an international program committee of high repute experts in the field, formed from
representatives of several eCommerce companies and academic institutions. Each submission was
reviewed by at least three reviewers. We would like to thank everyone who submitted a paper to
the workshop.
  In addition to presentation of a subset of accepted submissions, the workshop had two keynotes
by invited speakers from the industry, a poster session where all the accepted submissions were
presented, a panel discussion, and a group discussion.
   In the 2019 edition of this workshop we had a High Accuracy Recall Task challenge organized
and run by eBay search group. The challenge targets a common problem in eCommerce search:
Identifying the items to show when using non-relevance sorts such as by price, distance, recency
among others. The goal of this challenge was to draw attention of the research community to
the unique challenges posed by this problem. A total of sixteen teams participated in the data
challenge and several interesting solutions using state-of-the-art methods were used.
   We would like to thank the Program Committee members of the workshop for the their
participation and reviewing efforts. We would like to thank SIGIR for hosting us. We extend
our sincere gratitude to all the authors, presenters, and invited speakers for their contributions to
the material and productive discussions that formed an outstanding workshop.

                                                                                    Jon Degenhardt
                                                                                   Surya Kallumadi
                                                                                    Utkarsh Porwal
                                                                                   Andrew Trotman
                               P ROGRAM C OMMITTEE

• Eugene Agichtein, Emory University, USA
• Grigor Aslanyan, eBay, USA
• Kamelia Aryafar, Overstock, USA
• Gaetan Belbeoc’h, ADEO Group, France
• Anurag Bhardwaj, Apple, USA
• Sumit Borar, Google, India
• Eliot Brenner, Walmart, USA
• David Carmel, Amazon, Israel
• Young-Joo Chung, Rakuten, USA
• Bill de hÓra, Zalando, Ireland
• Arjen de Vries, Radboud University & Spinque, The Netherlands
• Kushal Dave, Microsoft, USA
• Ehsan Ebrahimzadeh, eBay, USA
• Shlomo Geva, QUT, Australia
• Liangjie Hong, Etsy, USA
• Murium Iqbal, Overstock, USA
• Jim Jansen, Qatar Computing Research Institute, Qatar
• Dietmar Jannach, Alpen-Adria-Universität Klagenfurt,Austria
• Faizan Javed, The Home Depot, USA
• Jaap Kamps, University of Amsterdam, The Netherlands
• Manojkumar Rangasamy Kannadasan, eBay, USA
• Ishita Khan, eBay, USA
• Tracy Holloway King, Adobe, USA
• Pranam Kolari, Walmart Labs, USA
• Mohit Kumar, Udaan, India
• Rohan Kumar, Flipkart, India
• Yiu-Chang Lin, Rakuten, USA
• Subhadeep Maji, Flipkart, India
• Shervin Malmasi, Amazon, USA
• Alistair Moffat, University of Melbourne, Australia
• Vito Ostuni, Pandora, USA
• Priyank Patel, Flipkart, India
• Owen Phelan, Zalando, Ireland
• Jeremy Pickens, Catalyst Repository Systems, USA
• Massimo Quadrana, Pandora, Italy
• Mahmuda Rahman, eBay, USA
• Tanay Saha, eBay, USA
• Ralf Schenkel, University of Trier, Germany
• Chris Severs, A9 (Amazon), USA
• Mohit Sharma, Walmart Labs, USA
• Parikshit Sondhi, Neulogic inc., USA
• Venkat Srinivasan, Virginia Tech., USA
• Thrivikrama Taula, Apple, USA
• Manos Tsagkias, 904Labs, The Netherlands
• Nicola Ueffing, eBay, Germany
• Nadia Vase, eBay, USA
• Musen Wen, Apple, USA
• Morgan White, The Home Depot, USA
• Tao Ye, Pandora, USA
• Sayyed Zahiri, The Home Depot, USA
• Huasha Zhao, Alibaba, USA