Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/iswc2007+aswc2007/tracks/research/papers/645> ?p ?o. }
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- 645 creator haofen-wang.
- 645 creator jie-zhang.
- 645 creator lei-zhang.
- 645 creator qiaoling-liu.
- 645 creator yong-yu.
- 645 creator yue-pan.
- 645 type InProceedings.
- 645 label "Semplore: An IR Approach to Scalable Hybrid Query of Semantic Web Data".
- 645 sameAs 645.
- 645 abstract "As an extension to the current Web, Semantic Web will not only contain structured data with machine understandable semantics but also textual information. While structured queries can be used to find information more precisely on the Semantic Web, keyword searches are still needed to help exploit textual information. It thus becomes very important that we can combine precise structured queries with imprecise keyword searches to have a hybrid query capability. In addition, due to the huge volume of information on the Semantic Web, the hybrid query must be processed in a very scalable way. In this paper, we define such a hybrid query capability that combines unary tree-shaped structured queries with keyword searches. We show how existing information retrieval (IR) index structures and functions can be reused to index semantic web data and its textual information, and how the hybrid query is evaluated on the index structure using IR engines in an efficient and scalable manner. We implemented this IR approach in an engine called Semplore. Comprehensive experiments on its performance show that it is a promising approach. It leads us to believe that it may be possible to evolve current web search engines to query and search the Semantic Web. Finally, we breifly describe how Semplore is used for searching Wikipedia and an IBM customer's product information.".
- 645 hasAuthorList authorList.
- 645 hasTopic Application_software.
- 645 hasTopic Data_management.
- 645 hasTopic Semantic_Web.
- 645 isPartOf proceedings.
- 645 title "Semplore: An IR Approach to Scalable Hybrid Query of Semantic Web Data".