Rough Ontology Based Semantic Information Retrieval

被引：0
|
作者：
Huang, Yinghui [1 ]
Li, Guanyu [1 ]
Li, Qiangqiang [1 ]
机构：
[1] Dalian Maritime Univ, Fac Informat Sci & Technol, Dalian, Peoples R China
来源：
2013 SIXTH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 1 | 2013年
关键词：
rough ontology; precise ontology; semantic information retrieval; semantic similarity;
D O I：
10.1109/ISCID.2013.23
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
It is known that traditional precise ontology based information retrieval cannot finish implicit semantic information mining. To solve this problem, rough ontology is introduced into semantic information retrieval to meet the user needs to utmost extent. Firstly, semantic information retrieval is defined and its advantages are analyzed in detail. Secondly, rough ontology is employed to extend precise ontology. Thirdly, rough ontology based the semantic information retrieval model and its semantic similarity calculation method is given. Finally, a rough ontology based semantic information retrieval system named as ROSRS is designed and its implementation method is given. The experimental results show that system ROSRS can retrieval information semantically not only from precise ontology but also from rough ontology, and the implicit information can be gotten. Furthermore, the recall ratio and precision ratio of retrieval results can be improved.
引用
收藏
页码：63 / 67
页数：5
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