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| Content Provider | ACM Digital Library |
|---|---|
| Author | Zhou, Guangyou Zhao, Jun Xie, Zhiwen He, Tingting Hu, Xiaohua Tony |
| Copyright Year | 2016 |
| Abstract | Community question answering (CQA) has become an increasingly popular research topic. In this paper, we focus on the problem of question retrieval. Question retrieval in CQA can automatically find the most relevant and recent questions that have been solved by other users. However, the word ambiguity and word mismatch problems bring about new challenges for question retrieval in CQA. State-of-the-art approaches address these issues by implicitly expanding the queried questions with additional words or phrases using monolingual translation models. While useful, the effectiveness of these models is highly dependent on the availability of quality parallel monolingual corpora (e.g., question--answer pairs) in the absence of which they are troubled by noise issues. In this work, we propose an alternative way to address the word ambiguity and word mismatch problems by taking advantage of potentially rich semantic information drawn from other languages. Our proposed method employs statistical machine translation to improve question retrieval and enriches the question representation with the translated words from other languages via non-negative matrix factorization. Experiments conducted on real CQA data sets show that our proposed approach is promising. |
| Starting Page | 1305 |
| Ending Page | 1314 |
| Page Count | 10 |
| File Format | |
| ISSN | 23299290 |
| e-ISSN | 23299304 |
| Volume Number | 24 |
| Issue Number | 7 |
| Journal | IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-07-01 |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Community question answering Information retrieval Natural language processing Question retrieval Text mining |
| Content Type | Text |
| Resource Type | Article |
| Subject | Instrumentation Computational Mathematics Signal Processing Electrical and Electronic Engineering Acoustics and Ultrasonics Speech and Hearing Media Technology |
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