A Clicked-URL Feature for Transactional Query Identification

Understanding query intents can help search engines to effectively improve their search quality. Click-through data has proven to be a valuable resource for query classification. In this paper, we propose a novel Clicked-URL (CURL) feature that uses semantic information extracted from user clicked U...

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Bibliographic Details
Published in2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) Vol. 1; pp. 950 - 951
Main Authors Sun, Yingcheng, Loparo, Kenneth
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2019
Subjects
Clicked URL feature
Feature extraction
Navigation
query identification
Search engines
search intent
Semantics
Software
Sun
transactional query
Uniform resource locators
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Summary:Understanding query intents can help search engines to effectively improve their search quality. Click-through data has proven to be a valuable resource for query classification. In this paper, we propose a novel Clicked-URL (CURL) feature that uses semantic information extracted from user clicked URLs in the search results, and compare with the "key word list" to identify transnational query type. Experiments show that we can obtain relatively high accuracy in transnational query identification with CURL, and achieve an improved performance in query classification combing with other features.
ISBN:9781728126074
172812607X
DOI:10.1109/COMPSAC.2019.00156