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http://dx.doi.org/10.9708/jksci.2017.22.02.97

SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval  

Jo, Dae Woong (School of Software, Soongsil University)
Kim, Myung Ho (School of Software, Soongsil University)
Abstract
In semantic information retrieval, we first need to build domain ontology and second, we need to convert the users' search keywords into a standard query such as SPARQL. In this paper, we propose a method that can automatically convert the users' search keywords into the SPARQL queries. Furthermore, our method can ensure effective performance in a specific domain such as law. Our method constructs the keyword history ontology by associating each keyword with a series of information when there are multiple keywords. The constructed ontology will convert keyword history ontology into SPARQL query. The automatic transformation method of SPARQL query proposed in the paper is converted into the query statement that is deemed the most appropriate by the user's intended keywords. Our study is based on the existing legal ontology constructions that supplement and reconstruct schema and use it as experiment. In addition, design and implementation of a semantic search tool based on legal domain and conduct experiments. Based on the method proposed in this paper, the semantic information retrieval based on the keyword is made possible in a legal domain. And, such a method can be applied to the other domains.
Keywords
Semantic web; Semantic information retrieval; Keyword search; SPARQL Query Transformation; Legal information retrieval;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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