Differential Query Semantic Analysis: Discovery of Explicit Interpretable Knowledge from E-Com Search Logs
Authors: 
Sahiti Labhishetty, ChengXiang Zhai, Min Xie, Lin Gong, Rahul Sharnagat, Satya ChemboluAuthors Info & Claims
Sahiti Labhishetty, ChengXiang Zhai, Min Xie, Lin Gong, Rahul Sharnagat, Satya ChemboluAuthors Info & ClaimsPages 535 - 543
Abstract
We present a novel strategy for analyzing E-Com search logs called Differential Query Semantic Analysis (DQSA) to discover explicit interpretable knowledge from search logs in the form of a semantic lexicon that makes context-specific mapping from a query segment (word or phrase) to the preferred attribute values of a product. Evaluation on a set of size-related query segments and attribute values shows that DQSA can effectively discover meaningful mappings of size-related query segments to their preferred specific attributes and attributes values in the context of a product type. DQSA has many uses including improvement of E-Com search accuracy by bridging the vocabulary gap, comparative analysis of search intent, and alleviation of the problem of tail queries and products.
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Index Terms
- Differential Query Semantic Analysis: Discovery of Explicit Interpretable Knowledge from E-Com Search Logs
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Published In
February 2022
1690 pages
ISBN:9781450391320
DOI:10.1145/3488560
- General Chairs:
- K. Selcuk Candan,
- Huan Liu,
- Program Chairs:
- Leman Akoglu,
- Xin Luna Dong,
- Jiliang Tang
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Published: 15 February 2022
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WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining
February 21 - 25, 2022
AZ, Virtual Event, USA
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