Abstract
Previous approaches to question retrieval in communitybased question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 736-739 |
| Number of pages | 4 |
| Journal | IEICE Transactions on Information and Systems |
| Volume | E92-D |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2009 Dec 1 |
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Keywords
- Community question answering
- Question retrieval
- Word semantic relatedness
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Software
- Artificial Intelligence
- Hardware and Architecture
- Computer Vision and Pattern Recognition
Cite this
Computing word semantic relatedness for question retrieval in community question answering. / Lee, Jung Tae; Song, Young In; Rim, Hae-Chang.
In: IEICE Transactions on Information and Systems, Vol. E92-D, No. 4, 01.12.2009, p. 736-739.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Computing word semantic relatedness for question retrieval in community question answering
AU - Lee, Jung Tae
AU - Song, Young In
AU - Rim, Hae-Chang
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Previous approaches to question retrieval in communitybased question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.
AB - Previous approaches to question retrieval in communitybased question answering rely on statistical translation techniques to match users' questions (queries) against collections of previously asked questions. This paper presents a simple but effective method for computing word relatedness to improve question retrieval based on word co-occurrence information directly extracted from question and answer archives. Experimental results show that the proposed approach significantly outperforms translation-based approaches.
KW - Community question answering
KW - Question retrieval
KW - Word semantic relatedness
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UR - http://www.scopus.com/inward/citedby.url?scp=77950358505&partnerID=8YFLogxK
U2 - 10.1587/transinf.E92.D.736
DO - 10.1587/transinf.E92.D.736
M3 - Article
AN - SCOPUS:77950358505
VL - E92-D
SP - 736
EP - 739
JO - IEICE Transactions on Information and Systems
JF - IEICE Transactions on Information and Systems
SN - 0916-8532
IS - 4
ER -