Automatic role‐explicit query extraction: a divide‐and‐conquer system leveraging on users' reformulating behaviors
Hai-Tao Yu, Fuji Ren · IEEJ Transactions on Electrical and Electronic Engineering · 2013
Abstract 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.