@article{ART002199605},
author={DaeWoong Jo and Myung-Ho Kim},
title={SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2017},
volume={22},
number={2},
pages={97-104},
doi={10.9708/jksci.2017.22.02.97}
TY - JOUR
AU - DaeWoong Jo
AU - Myung-Ho Kim
TI - SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval
JO - Journal of The Korea Society of Computer and Information
PY - 2017
VL - 22
IS - 2
PB - The Korean Society Of Computer And Information
SP - 97
EP - 104
SN - 1598-849X
AB - 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.
KW - Semantic web;Semantic information retrieval;Keyword search;SPARQL Query Transformation;Legal information retrieval
DO - 10.9708/jksci.2017.22.02.97
ER -
DaeWoong Jo and Myung-Ho Kim. (2017). SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval. Journal of The Korea Society of Computer and Information, 22(2), 97-104.
DaeWoong Jo and Myung-Ho Kim. 2017, "SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval", Journal of The Korea Society of Computer and Information, vol.22, no.2 pp.97-104. Available from: doi:10.9708/jksci.2017.22.02.97
DaeWoong Jo, Myung-Ho Kim "SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval" Journal of The Korea Society of Computer and Information 22.2 pp.97-104 (2017) : 97.
DaeWoong Jo, Myung-Ho Kim. SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval. 2017; 22(2), 97-104. Available from: doi:10.9708/jksci.2017.22.02.97
DaeWoong Jo and Myung-Ho Kim. "SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval" Journal of The Korea Society of Computer and Information 22, no.2 (2017) : 97-104.doi: 10.9708/jksci.2017.22.02.97
DaeWoong Jo; Myung-Ho Kim. SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval. Journal of The Korea Society of Computer and Information, 22(2), 97-104. doi: 10.9708/jksci.2017.22.02.97
DaeWoong Jo; Myung-Ho Kim. SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval. Journal of The Korea Society of Computer and Information. 2017; 22(2) 97-104. doi: 10.9708/jksci.2017.22.02.97
DaeWoong Jo, Myung-Ho Kim. SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval. 2017; 22(2), 97-104. Available from: doi:10.9708/jksci.2017.22.02.97
DaeWoong Jo and Myung-Ho Kim. "SPARQL Query Automatic Transformation Method based on Keyword History Ontology for Semantic Information Retrieval" Journal of The Korea Society of Computer and Information 22, no.2 (2017) : 97-104.doi: 10.9708/jksci.2017.22.02.97