@inproceedings{7d89c753888b494184b98b07e344ecde,
title = "Differential query semantic analysis: Discovery of explicit interpretable knowledge from e-com search logs",
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.",
keywords = "E-com search logs, Query difference analysis, Query word lexicon",
author = "Sahiti Labhishetty and Zhai, {Cheng Xiang} and Min Xie and Lin Gong and Rahul Sharnagat and Satya Chembolu",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 15th ACM International Conference on Web Search and Data Mining, WSDM 2022 ; Conference date: 21-02-2022 Through 25-02-2022",
year = "2022",
month = feb,
day = "11",
doi = "10.1145/3488560.3498503",
language = "English (US)",
series = "WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining",
publisher = "Association for Computing Machinery",
pages = "535--543",
booktitle = "WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining",
address = "United States",
}