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| Content Provider | ACM Digital Library |
|---|---|
| Author | Jensen, Christian S. Yuan, Quan Cao, Xin Cong, Gao Cui, Bin |
| Copyright Year | 2012 |
| Abstract | Community Question Answering (CQA) is a popular type of service where users ask questions and where answers are obtained from other users or from historical question-answer pairs. CQA archives contain large volumes of questions organized into a hierarchy of categories. As an essential function of CQA services, question retrieval in a CQA archive aims to retrieve historical question-answer pairs that are relevant to a query question. This article presents several new approaches to exploiting the category information of questions for improving the performance of question retrieval, and it applies these approaches to existing question retrieval models, including a state-of-the-art question retrieval model. Experiments conducted on real CQA data demonstrate that the proposed techniques are effective and efficient and are capable of outperforming a variety of baseline methods significantly. |
| Starting Page | 1 |
| Ending Page | 38 |
| Page Count | 38 |
| File Format | |
| ISSN | 10468188 |
| e-ISSN | 15582868 |
| DOI | 10.1145/2180868.2180869 |
| Volume Number | 30 |
| Issue Number | 2 |
| Journal | ACM Transactions on Information Systems (TOIS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-05-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Question-answering services Categorization Cluster-based retrieval Question search |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science Applications Information Systems Business, Management and Accounting |
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