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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hao Hu Mingxi Zhang Zhenying He Peng Wang Wei Wang |
| Copyright Year | 2013 |
| Description | Author affiliation: Sch. of Comput. Sci., Fudan Univ., Shanghai, China (Hao Hu; Mingxi Zhang; Zhenying He; Peng Wang; Wei Wang) |
| Abstract | Diversifying query suggestions has emerged recently, by which the recommended queries can be both relevant and diverse. Most existing works diversify suggestions by query log analysis, however, for structured data, not all query logs are available. To this end, this paper studies the problem of suggesting diverse query terms by using topics from Wikipedia. Wikipedia is a successful online encyclopedia, and has high coverage of entities and concepts. We first obtain all relevant topics from Wikipedia, and then map each term to these topics. As the mapping is a nontrivial task, we leverage information from both Wikipedia and structured data to semantically map each term to topics. Finally, we propose a fast algorithm to efficiently generate the suggestions. Extensive evaluations are conducted on a real dataset, and our approach yields promising results. |
| Starting Page | 139 |
| Ending Page | 146 |
| File Size | 314332 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9780769551456 |
| DOI | 10.1109/WI-IAT.2013.21 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-11-17 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Electronic publishing query suggestion diversification Databases topics Encyclopedias Wikipedia Internet Association rules |
| Content Type | Text |
| Resource Type | Article |
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