Premium
Automatic role‐explicit query extraction: a divide‐and‐conquer system leveraging on users' reformulating behaviors
Author(s) -
Yu Haitao,
Ren Fuji
Publication year - 2014
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21937
Subject(s) - computer science , session (web analytics) , divide and conquer algorithms , key (lock) , process (computing) , word (group theory) , web query classification , query language , information retrieval , web search query , world wide web , search engine , algorithm , mathematics , programming language , geometry , computer security
This paper presents a system that can automatically extract role‐explicit queries from a query log without any human intervention. The key idea underlying our system is as follows: We perform a divide‐and‐conquer process through differentiating the sessions in a query log as mul‐sessions and sin‐sessions. According to the session type, different approaches are proposed. We translate the contextual information in mul‐sessions as indirect human wisdom to facilitate role‐explicit query extraction on mul‐sessions. Furthermore, leveraging on the role‐explicit queries extracted from mul‐sessions, we learn the simplified word n‐gram role model (SWNR) to facilitate role‐explicit query extraction on sin‐sessions. The experimental results show that our proposed system is clearly favored by the indirect human wisdom hidden in mul‐sessions and achieves a satisfactory performance, namely more than 79% in terms of different metrics. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.