Differential Query Semantic Analysis: Discovery of Explicit Interpretable Knowledge from E-Com Search Logs

被引:1
|
作者
Labhishetty, Sahiti [1 ]
Zhai, ChengXiang [1 ]
Xie, Min [2 ]
Gong, Lin [2 ]
Sharnagat, Rahul [2 ]
Chembolu, Satya [2 ]
机构
[1] Univ Illinois, Champaign, IL 61820 USA
[2] WalmartLabs, San Bruno, CA USA
关键词
Query word lexicon; E-Com Search Logs; Query difference analysis;
D O I
10.1145/3488560.3498503
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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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页码:544 / 552
页数:9
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