DocumentCode
2028606
Title
Ranked keyword query on Semantic Web data
Author
Li, Huiying ; Wang, Yanbing
Author_Institution
Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing, China
Volume
5
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
2285
Lastpage
2289
Abstract
The growth of the Semantic Web has seen a rapid increase in the amount of Semantic Web data. Meanwhile, the demand for access to Semantic Web data without detailed knowledge of RDF query languages is increasing. In this paper, an approach which can return ranked answers to keyword query without the help of data schema is proposed. With the proposed approach, Semantic Web data is modeled as RDF sentence graph, and an answer to a query is modeled as an RDF sentence tree containing all query keywords. We present an algorithm for searching top-k answers based on an indexing scheme, and employ IR-style scores in re-ranking answers. The experimental results show our approach is feasible and effective.
Keywords
indexing; query processing; semantic Web; IR-style scores; RDF query languages; RDF sentence graph; indexing scheme; ranked keyword query; semantic web data; top-k answers; Data models; Indexes; Keyword search; Resource description framework; Semantics; Silicon;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5931-5
Type
conf
DOI
10.1109/FSKD.2010.5569309
Filename
5569309
Link To Document