The 2019 SIGIR Workshop On eCommerce

July 25, Paris, France


The SIGIR Workshop on eCommerce will serve as a platform for publication and discussion of Information Retrieval and NLP research & their applications in the domain of eCommerce. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to product search and recommendation in eCommerce.

SIGIR eCom is a full day workshop taking place on Thursday, July 25, 2019 in conjunction with SIGIR 2019 in Paris, France.

Keynote Speakers

Eugene Agichtein, Emory University (USA)

Modeling Explicit and Implicit User Behavior for Finding Answers on the Web
Abstract: Billions of people interact with Web search engines and online forums. These data can be used to derive models of searcher intent, attention, and satisfaction, and, in turn to improve question answering tasks, such as candidate passage retrieval, answer selection, and presentation. I will describe how explicit interactions captured using lightweight instrumentation of both search- and landing pages can be converted to attention and satisfaction signals. Then, I will discuss how these signals can be used to improve selection of relevant documents, passages, and answers, and our initial work on adapting these ideas to new interaction modalities.

Speaker Bio

Dr. Eugene Agichtein is a Winship Associate Professor of Computer Science at Emory University in Atlanta, USA, where he leads the Intelligent Information Access Laboratory (IR Lab). Since January 2019, he has been a part-time "Amazon Scholar” at Amazon. Eugene's research spans the areas of information retrieval, natural language processing, data mining, and human computer interaction, most recently focusing on conversational search. Together with great colleagues and students, Eugene published over 100 papers, and has been recognized by multiple awards, including the A.P. Sloan fellowship and the 2013 Karen Spark Jones Award from the British Computer Society, and "test of time" awards from the SIGIR and WSDM conference. He was Program Co-Chair of the WSDM 2012 and WWW 2017 conferences.

Xin Luna Dong, Amazon (USA)

Building a Broad Knowledge Graph for Products
Abstract: Knowledge graphs have been used to support a wide range of applications and enhance search results for multiple major search engines, such as Google and Bing. At Amazon we are building a Product Graph, an authoritative knowledge graph for all products in the world. The thousands of product verticals we need to model, the vast number of data sources we need to extract knowledge from, the huge volume of new products we need to handle every day, and the various applications in Search, Discovery, Personalization, Voice, that we wish to support, all present big challenges in constructing such a graph.

In this talk we describe our efforts in building a broad product graph, a graph that starts shallow with core entities and relationships, and allows easily adding verticals and relationships in a pay-as-you-go fashion. We describe our efforts on knowledge extraction, linkage, and cleaning to significantly improve the coverage and quality of product knowledge. We also present our progress towards our moon-shot goals including harvesting knowledge from the web, hands-off-the-wheel knowledge integration and cleaning, human-in-the-loop knowledge learning, and graph mining and graph-enhanced search.

Speaker Bio

Dr. Xin Luna Dong is a Principal Scientist at Amazon, leading the efforts of constructing Amazon Product Knowledge Graph. She was one of the major contributors to the Google Knowledge Vault project, and has led the Knowledge-based Trust project, which is called the “Google Truth Machine” by Washington’s Post. She has co-authored book “Big Data Integration”, was awarded ACM Distinguished Member, VLDB Early Career Research Contribution Award for "advancing the state of the art of knowledge fusion", and Best Demo award in Sigmod 2005. She serves in VLDB endowment and PVLDB advisory committee, and is a PC co-chair for VLDB 2021, ICDE Industry 2019, VLDB Tutorial 2019, Sigmod 2018 and WAIM 2015.

Panel Discussion

Topic: Ecommerce Discovery vs Web Search: Same or Different?
Vanessa Murdock

Estelle Afshar
The Home Depot
David Carmel
Charles Clarke
University of Waterloo
Xin Luna Dong

SIGIR eCom'19 Workshop Schedule

Paris | Cité des Sciences et de l'industrie | Room: Louis Armand Est (Level S3)
Morning Session
8:55 am Opening Remarks
9:00 am
Keynote 1
Modeling Explicit and Implicit User Behavior for Finding Answers on the Web
Eugene Agichtein
9:50 am Contributed Talk
Multi-objective Relevance Ranking
Michinari Momma, Alireza Bagheri Garakani and Yi Sun
10:10 am Contributed Talk
Learning Embeddings for Product Size Recommendations
Kallirroi Dogani, Matteo Tomassetti, Saúl Vargas, Ben Chamberlain and Sofie de Cnudde
10:30 am Coffee Break
11:00 am Contributed Talk
Leverage Implicit Feedback for Context-aware Product Search
Keping Bi, Choon Hui Teo, Yesh Dattatreya, Vijai Mohan and W. Bruce Croft
11:20 am Short Talks: Ideas & Insights
Omar Alonso
David Carmel
Owen Phelan
12:30 pm Lunch Break
Afternoon Session
1:30 pm
Keynote 2
Building a Broad Knowledge Graph for Products
Xin Luna Dong
2:15 pm Panel Discussion
Ecommerce Discovery vs Web Search: Same or Different?
Vanessa Murdock     Amazon, USA
Estelle Afshar     The Home Depot, USA
David Carmel     Amazon, Israel
Charles Clarke     University of Waterloo, Canada
Xin Luna Dong     Amazon, USA
3:00 pm Coffee Break
3:30 pm
Report on SIGIR eCom'19 High Accuracy Recall Task
Jon Degenhardt
3:50 pm Group Discussion
4:05 pm Poster Session
5:30 pm Closing


Paris | Cité des Sciences et de l'industrie | Room: Louis Armand Est (Level S3) | Venue