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| Content Provider | Springer Nature Link |
|---|---|
| Author | Yan, Li Ma, Ruizhe Li, Dazhen Cheng, Jingwei |
| Copyright Year | 2017 |
| Abstract | In this paper, we propose a query relaxation approach to handle the problem of empty or too little answers returned from RDF query. We apply RDF entailment to triple patterns in the original query to get more general answers. We propose the notion of semantic similarity degree so that the returned answers are semantically close to the original query. We present how to compute the semantic similarity degree of a relaxed query with respect to the original query. With the semantic similarity degrees, we can choose the relaxed queries that are semantically close to the original query. On this basis, we give the query relaxation algorithm. We verify our approach by experiments. It is shown that our approach of RDF query relaxation based on the semantic similarity degree has some good performances and is feasible. |
| Ending Page | 491 |
| Page Count | 11 |
| Starting Page | 481 |
| File Format | |
| ISSN | 0010485X |
| e-ISSN | 14365057 |
| Journal | Computing |
| Issue Number | 5 |
| Volume Number | 99 |
| Language | English |
| Publisher | Springer Vienna |
| Publisher Date | 2017-04-13 |
| Publisher Place | Vienna |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Information Systems Applications (incl.Internet) RDF Query relaxation Semantics Software Engineering Computer Application in Administrative Data Processing Computer Science Artificial Intelligence (incl. Robotics) Computer Communication Networks Approximate query Semantic similarity degree |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Computational Theory and Mathematics Computational Mathematics Numerical Analysis Computer Science Applications Software |
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