Over the past few years, consumer behavior has shifted from traditional in-store shopping to online shopping. For example, eCommerce sales have grown from around 5% of total US sales in 2012 to around 15.4% in year 2023. This rapid growth of eCommerce has created new challenges and vital new requirements for intelligent information retrieval systems.
Scalable systems
Since the pandemic hit, eCommerce became an important part of people’s routine and they started using online shopping for smallest grocery items to big electronics as well as cars. With such a large assortment of products and millions of users, achieving higher scalability without losing accuracy is a leading concern for information retrieval systems for eCommerce.
Interactive Systems
The diverse buyers make the relevance of the results highly subjective, because relevance varies for different buyers. The most suitable and intuitive solution to this problem is to make the system interactive and provide correct relevance for different users. Hence, interactive information retrieval systems are becoming necessity in eCommerce.
System improvement
To handle sudden change in buyers’ behavior, industries adopted existing sub-optimal in- formation retrieval techniques for various eCommerce tasks. Parallelly, they also started exploring/researching for better solutions and in dire need of help from research community
The objective of this workshop is to bring a diverse set of practitioners and researchers together and encourage them to share their ideas, challenges & solutions and research. This workshop will provide a forum to discuss and learn the latest trends for interactive and scalable information retrieval approaches for eCommerce.
This workshop will provide a forum to discuss and learn the latest trends for interactive and scalable information retrieval approaches for eCommerce. It will provide academic and industrial researchers a platform to present their latest works, share research ideas, present and discuss various challenges, and identify the areas where further research is needed. It will foster the development of a a research community focused on solving eCommerce-related information retrieval problems that provide superior eCommerce experience to all users.
Topics of interest include, but are not limited to:
All papers will be peer reviewed (single-blind) by the program committee and judged by their relevance to the workshop, especially to the main themes identified above, and their potential to generate discussion.
All submissions must be in PDF format according to the latest ACM template published in the ACM guidelines (two column format). Please select the generic “sigconf” sample and for blind manuscript submission recommended setting for Latex file of manuscript is: \documentclass[sigconf, anonymous, review]{acmart}. The PDF files must have all non-standard fonts embedded. Submissions must describe work that is not previously published, and not currently under review elsewhere. All submissions must be in English. We invite you all to contribute: full research papers (up to 10+2 pages) and short papers (up to 5+1 pages). Full workshop papers should not exceed 12 pages in length (maximum 8 pages for the main paper content + maximum 2 pages for appendixes + maximum 2 pages for references).
Please note that at least one of the authors of each accepted paper must register to WSDM conference to present the paper during the ISIR-eCom 2024 workshop.
Submissions to ISIR-eCom 2024 workshop should be made at easychair.
Submissions Due | |
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Notification | Feb 01 |
Camera Ready Version Due | Feb 23 |
Workshop Day | March 08 |
Time | Talk | Title |
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9:00am - 9:15am | Opening Remarks | Welcome to ISIR-eCom |
9:15am - 10:00am | Invited Talk 1 - Ching-Wei Chen | Real-world Applications of LLMs for eCommerce. |
Coffee Break | ||
10:30am - 11:15am | Invited Talk 2 - Mahashweta Das | Machine Learning for Financial Transaction Data: A Recommendation Use Case. |
11:15am - 12:00pm | Invited Talk 3 - Prof. Pan Li | Dual Learning: Bridging Knowledge Between LLM and Recommender System. |
Lunch Break | ||
01:30pm - 02:15pm | Invited Talk 3 - Luna Dong | Generations of Knowledge Graphs: The Crazy Ideas and The Business. |
02:15pm - 02:30pm | Paper 1 | Captions Are Worth a Thousand Words: Enhancing Product Retrieval with Pretrained Image-to-Text Models. |
02:30pm - 02:45pm | Paper 2 | Point-of-interest Re-ranking by Modeling Session Context and Geography-semantics Interaction. |
02:45pm - 03:00pm | Paper 3 | DeepMMATE: Deep learning based MultiModal architecture for Audit Taxability classification with XAI. |
03:00pm - 03:15pm | Paper 4 | CAPS: A Practical Partition Index for Filtered Similarity Search. |
3:15pm - 3:30pm | Paper 5 | Multi-objective Neural Retrieval for Query AutoComplete. |
03:30pm - 03:05pm | Closing Notes |
Principal Scientist
Meta Reality Labs, CA
Vice President
Crossing Minds, CA
Assistant Professor
Georgia Institute of Technology, GA
Senior Director
Visa Research, CA
Speaker | Title |
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Luna Dong | Generations of Knowledge Graphs: The Crazy Ideas and The Business [presentation] [Abstract]
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Ching-Wei Chen | Real-world Applications of LLMs for eCommerce [presentation] [Abstract]
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Prof. Pan Li | Dual Learning: Bridging Knowledge Between LLM and Recommender System [presentation] [Abstract]
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Mahashweta Das | Machine Learning for Financial Transaction Data: A Recommendation Use Case [Abstract]
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Walmart Global Tech
Sunnyvale, CA
Salesforce
San Francisco, CA
The Home Depot
Atlanta, GA
Amazon
Seattle, WA
University of Massachusetts Amherst
Amherst, MA
Pinterest
New York, NY
University of Minnesota Twin Cities
MN
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Please send questions and enquiries to isir.ecom.workshop@gmail.com.