摘要
为了实现精确本体无法完成的信息的隐含语义挖掘,检索到满足用户请求的信息,引入粗糙本体实现对信息语义检索的支持。剖析了基于精确本体的信息语义检索的过程及其不足,引入了粗糙本体以扩展精确本体,阐述了粗糙本体支持的信息语义检索的理论模型、设计了语义相似度算法,给出了模型实现方法。实验结果表明,该检索方法较之精确本体支持的语义检索和基于关键词的语法检索具有更好的检索效果。
To accomplish information implied semantic mining that precise-ontology-based retrieval cannot, and meet the needs of the user, rough ontology is introduced to support information semantic retrieval. Firstly, the precise-ontology-based information semantic retrieval process and its shortage are analyzed; secondly, the rough ontology is introduced to expand the precise ontology; thirdly, the rough-ontology-based semantic information retrieval model theoretically is expounded, the semantic similarity algo- rithm and the model realization method is put forward; finally, an example is conducted to show that its result is better than the both tow methods based on precise-ontology and keywords.
出处
《计算机工程与设计》
CSCD
北大核心
2012年第12期4711-4715,4730,共6页
Computer Engineering and Design
基金
国家自然科学基金项目(60972090)
关键词
粗糙本体
精确本体
信息检索
信息语义检索
语义相似度
rough ontology
precise ontology
information retrieval
information semantic retrieval
semantic similarity
