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Enhanced SPARQL-based design rationale retrieval

Li, Luye, Gao, Shuming, Liu, Ying and Qin, Xiaolian 2016. Enhanced SPARQL-based design rationale retrieval. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 30 (4) , pp. 406-423. 10.1017/S089006041600038X

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Abstract

Design rationale (DR) is an important category within design knowledge, and effective reuse of it depends on its successful retrieval. In this paper, an ontology-based DR retrieval approach is presented, which allows users to search by entering normal queries such as questions in natural language. First, an ontology-based semantic model of DR is developed based on the extended issue-based information system-based DR representation in order to effectively utilize the semantics embedded in DR, and a database of ontology-based DR is constructed, which supports SPARQL queries. Second, two SPARQL query generation methods are proposed. The first method generates initial SPARQL queries from natural language queries automatically using template matching, and the other generates initial SPARQL queries automatically from DR record-based queries. In addition, keyword extension and optimization is conducted to enhance the SPARQL-based retrieval. Third, a design rationale retrieval prototype system is implemented. The experimental results show the advantages of the proposed approach.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Publisher: Cambridge University Press (CUP)
ISSN: 0890-0604
Date of First Compliant Deposit: 19 October 2016
Date of Acceptance: 4 October 2016
Last Modified: 10 Jul 2017 01:44
URI: http://orca.cf.ac.uk/id/eprint/95462

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