Practical and effective IR-style keyword search over semantic web |
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| Authors: | Xiaomin Ning Hai Jin Weijia Jia Pingpeng Yuan |
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| Institution: | 1. China Ship Development and Design Center, Wuhan 430064, China;2. Services Computing Technology and System Laboratory, Cluster and Grid Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;3. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong |
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| Abstract: | This paper presents a novel IR-style keyword search model for semantic web data retrieval, distinguished from current retrieval methods. In this model, an answer to a keyword query is a connected subgraph that contains all the query keywords. In addition, the answer is minimal because any proper subgraph can not be an answer to the query. We provide an approximation algorithm to retrieve these answers efficiently. A special ranking strategy is also proposed so that answers can be appropriately ordered. The experimental results over real datasets show that our model outperforms existing possible solutions with respect to effectiveness and efficiency. |
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| Keywords: | Group Steiner tree Keyword search RDF graph Top-K |
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