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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Song Jin Hongfei Lin Sui Su |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Computer Science and Engineering, Dalian University of Technology, 116024, China (Song Jin; Hongfei Lin; Sui Su) |
| Abstract | In traditional query expansion techniques, we choose the expansion terms based on their weights in the relevant documents. However, this kind of approaches does not take into account the semantic relationship between the original query terms and the expansion terms. Folksonomy is a social service in Web 2.0, which provides a large amount of social annotations. As the core of folksonomy, tags are high quality descriptors of the information contents and topics. Moreover, different tags describing the same information resource are semantically related to some extent. In this paper, we propose a query expansion method that utilizes the tag co-occurrence information to select the most appropriate expansion terms. Experimental results show that our tag co-occurrence-based query expansion technique consistently improves retrieval performance, compared with no-expansion method. This means the expansion terms we selected are semantically related to the original query, and tags of folksonomy will be the new resource of expansion terms. |
| Starting Page | 300 |
| Ending Page | 305 |
| File Size | 101231 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424448302 |
| DOI | 10.1109/GRC.2009.5255110 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-17 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer science Information resources Text analysis Feedback Keyword search Web pages Thesauri Data mining Web sites Online Communities/Technical Collaboration |
| Content Type | Text |
| Resource Type | Article |
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