Ontology-based semantic retrieval for engineering domain knowledge

被引:32
|
作者
Zhang, Xutang [1 ]
Hou, Xin [1 ]
Chen, Xiaofeng [1 ]
Zhuang, Ting [1 ]
机构
[1] Harbin Inst Technol, Sch Mechatron Engn, Harbin 150001, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Ontology; Knowledge retrieval; Latent semantic analysis; Document clustering; MODEL;
D O I
10.1016/j.neucom.2011.12.057
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The semantic retrieval of the engineering domain knowledge is critical in many engineering activities, e.g., product design and process planning. To address the problems with existing keyword-based and semantic-enable methods, we propose an ontology-based semantic retrieval scheme for knowledge search and retrieval from domain documents. In our scheme, domain ontology is first constructed using the graph-based approach to automating construction of domain ontology GRAONTO proposed by our group, and query semantic extension and retrieval are then adopted for semantic-based knowledge retrieval. For query semantic extension, latent semantic analysis is adopted to discover the latent semantic relationships between queries and ontology semantic features, and ontology semantic graph is used to represent the query. For semantic retrieval, a graph-based k-means method is proposed to partition the domain documents into several clusters, and a hierarchical searching strategy is employed for document retrieval. Finally, experimental results on the fixture design corpus verify the benefits of the proposed scheme. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:382 / 391
页数:10
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