Semantic inference based on ontology for medical FAQ mining

被引：0

作者：

Yeh, JF ^{[1
]}

Chen, MJ ^{[1
]}

Wu, CH ^{[1
]}

机构：

[1] Natl Cheng Kung Univ, Dept Comp Sci & Informat Engn, Tainan 70101, Taiwan

来源：

2003 INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND KNOWLEDGE ENGINEERING, PROCEEDINGS | 2003年

关键词：

FAQ; question stemming; latent semantic analysis; ontology; semantic inference;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents an approach to semantic inference for FAQ mining based on ontology. The questions are classified into ten intension categories using predefined question stemming keywords. The answers in the FAQ database are also clustered using latent semantic analysis (LSA) and K-means algorithm. For FAQ mining, given a query, the question part and answer part in an FAQ question-answer pair is matched with the input query, respectively. Finally, the probabilities estimated from these two parts are integrated and used to choose the most likely answer for the input query. These approaches are experimented on a medical FAQ system. The results show. that the proposed approach achieved a retrieval rate of 90% and outperformed the. keyword-based approach.

引用

页码：710 / 715

页数：6