579 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- eBay (Ireland)IE3 papers
- Google (United States)US3 papers
- Centrum Wiskunde & InformaticaNL2 papers
- Georgia Institute of TechnologyUS2 papers
- Nanyang Technological UniversitySG2 papers
- National University of SingaporeSG2 papers
- Pennsylvania State UniversityUS2 papers
- University of Science and Technology of ChinaCN2 papers
- Amazon (United States)US1 paper
- Athens University of Economics and BusinessGR1 paper
- Atlanta Technical CollegeUS1 paper
- Brown UniversityUS1 paper
11 papers · 1 filter
Improving Search Suggestions for Alphanumeric Queries
Samarth Agrawal, Jayanth Yetukuri, Diptesh Kanojia +2
Alphanumeric identifiers such as manufacturer part numbers (MPNs), SKUs, and model codes are ubiquitous in e-commerce catalogs and search. These identifiers are sparse, non linguis…
Progressive Refinement of E-commerce Search Ranking Based on Short-Term Activities of the Buyer
Taoran Sheng, Sathappan Muthiah, Atiq Islam +1
In e-commerce shopping, aligning search results with a buyer's immediate needs and preferences presents a significant challenge, particularly in adapting search results throughout…
BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations
Ashirbad Mishra, Jinyu Zhao, Soumik Dey +3
In the domain of sponsored search advertising, the focus of Keyphrase recommendation has largely been on exact match types, which pose issues such as high management expenses, limi…
To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay
Soumik Dey, Hansi Wu, Binbin Li
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). The relevance of advertiser keyphrases p…
Middleman Bias in Advertising: Aligning Relevance of Keyphrase Recommendations with Search
Soumik Dey, Wei Zhang, Hansi Wu +2
E-commerce sellers are recommended keyphrases based on their inventory on which they advertise to increase buyer engagement (clicks/sales). Keyphrases must be pertinent to items; o…
GraphEx: A Graph-based Extraction Method for Advertiser Keyphrase Recommendation
Ashirbad Mishra, Soumik Dey, Marshall Wu +5
Online sellers and advertisers are recommended keyphrases for their listed products, which they bid on to enhance their sales. One popular paradigm that generates such recommendati…
Merchandise Recommendation for Retail Events with Word Embedding Weighted Tf-idf and Dynamic Query Expansion
Ted Tao Yuan, Zezhong Zhang
To recommend relevant merchandises for seasonal retail events, we rely on item retrieval from marketplace inventory. With feedback to expand query scope, we discuss keyword expansi…
Learning Intents behind Interactions with Knowledge Graph for Recommendation
Xiang Wang, Tinglin Huang, Dingxian Wang +4
Knowledge graph (KG) plays an increasingly important role in recommender systems. A recent technical trend is to develop end-to-end models founded on graph neural networks (GNNs).…
Efficient and Effective Query Auto-Completion
Simon Gog, Giulio Ermanno Pibiri, Rossano Venturini
Query Auto-Completion (QAC) is an ubiquitous feature of modern textual search systems, suggesting possible ways of completing the query being typed by the user. Efficiency is cruci…
Position Bias Estimation for Unbiased Learning-to-Rank in eCommerce Search
Grigor Aslanyan, Utkarsh Porwal
The Unbiased Learning-to-Rank framework has been recently proposed as a general approach to systematically remove biases, such as position bias, from learning-to-rank models. The m…
Explainable Reasoning over Knowledge Graphs for Recommendation
Xiang Wang, Dingxian Wang, Canran Xu +3
Incorporating knowledge graph into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity be…