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New Technology of Library and Information Service  2014, Vol. 30 Issue (9): 44-50    DOI: 10.11925/infotech.1003-3513.2014.09.06
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Research on Intelligent Retrieval of Complex Product Design Knowledge
Ma Xukai, Ding Shengchun
College of Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, China
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[Objective] Product design knowledge is obtained as fast and accurate as possible in order to meet complex product design process needs. [Methods] Use Ontology as knowledge representation model to organize and represent product design knowledge so as to provide a common understand of product design knowledge. Use Bayesian algorithm to identify the type of retrieval questions in order to reduce the scope of the candidate questions calculate keywords similarity between retrieval question and candidate questions based on TF and cosine similarity, calculate syntax similarity based on word forms and sentence length of retrieval question. [Results] Test result shows that accuracy rate is 91.3%, the recall rate is 86.2%, and accuracy rate better than other algorithms. [Limitations] Search result depends on the number of candidate questions. For large-scale data, complexity of similarity algorithm is very high, and the algorithm needs further optimization. [Conclusions] The method is effective and has a positive significance for identifying the type of questions and similarity computation.

Key wordsComplex product      Ontology      Knowledge representation      Similarity      Knowledge retrieval      Barrel     
Received: 24 March 2014      Published: 20 October 2014
:  TP391  

Cite this article:

Ma Xukai, Ding Shengchun. Research on Intelligent Retrieval of Complex Product Design Knowledge. New Technology of Library and Information Service, 2014, 30(9): 44-50.

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