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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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Abstract  

[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 words： Complex product      Ontology      Knowledge representation      Similarity      Knowledge retrieval      Barrel     
Received: 24 March 2014      Published: 20 October 2014
:  TP391  
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Ma Xukai
Ding Shengchun

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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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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2014.09.06     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2014/V30/I9/44

[1] 余旭, 刘继红, 何苗. 基于领域本体的复杂产品设计知识检索技术[J]. 计算机集成制造系统, 2011, 17(2): 225-231. (Yu Xu, Liu Jihong, He Miao. Design Knowledge Retrieval Technology Based on Domain Ontology for Complex Products [J]. Computer Integrated Manufacturing System, 2011, 17(2): 225-231.)
[2] 张功杰, 赵向军, 陈克建. 面向本体的语义相似度计算及在检索中的应用[J]. 计算机工程与应用, 2010, 46(29): 131-133. (Zhang Gongjie, Zhao Xiangjun, Chen Kejian. Ontology Oriented Semantic Similarity Calculation and Application in Retrieval [J]. Computer Engineering and Applications, 2010, 46(29): 131-133.)
[3] Jin H M, Peng W L. Study on Product Design and Development Based on Design Knowledge Base [C]. In: Proceedings of the 2nd International Symposium on Computational Intelligence and Design. 2009: 463-467.
[4] Chen S, Yan Y, Wang G. Product-Design Knowledge Retrieval Based on Ontology and Rule [C]. In: Proceedings of the 2nd International Conference on Computer Engineering and Application. 2011: 285-290.
[5] 贾雪峰, 王建新, 齐建东, 等. 基于领域本体的智能检索模型[J]. 计算机工程, 2010, 36(23): 171-174. (Jia Xuefeng, Wang Jianxin, Qi Jiandong, et al. Intelligent Retrieval Model Based on Domain Ontology [J]. Computer Engineering, 2010, 36(23): 171-174.)
[6] 孟红伟, 张志平, 张晓丹. 基于领域本体的文献智能检索模型研究[J]. 情报杂志, 2013, 32(9): 180-184. (Meng Hongwei, Zhang Zhiping, Zhang Xiaodan. Research on Intelligent Information Retrieval Model Based on Domain Ontology [J]. Journal of Intelligence, 2013, 32(9): 180-184.)
[7] 曹灵莉, 陈扬, 张雷. 基于本体的产品绿色设计知识检索方法研究[J]. 合肥工业大学学报: 自然科学版, 2013, 36(5): 513-518. (Cao Lingli, Chen Yang, Zhang Lei. Study of Knowledge Retrieval During Product Green Design Based on Ontology [J]. Journal of Hefei University of Technology: Natural Science, 2013, 36(5): 513-518.)
[8] Wang R, Wang X H, Chi Z R, et al. Chinese Sentence Similarity Measure Based on Words and Structure Information [C]. In: Proceedings of International Conference on Advanced Language Processing and Web Information Technology. 2008: 27-31.
[9] 董自涛, 包佃清, 马小虎. 智能问答系统中问句相似度计算方法[J]. 武汉理工大学学报: 信息与管理工程版, 2010, 32(1): 31-34. (Dong Zitao, Bao Dianqing, Ma Xiaohu. Question Similarity Computing in Intelligent Question Answering System [J]. Journal of WUT: Information & Management Engineering, 2010, 32(1): 31-34.)
[10] Moreda P, Llorens H, Saquete E, et al. Combining Semantic Information in Question Answering Systems [J]. Information Processing and Management, 2011, 47(6): 870-885.
[11] 张亮, 冯冲, 陈肇雄, 等. 基于语句相似度计算的FAQ自动回复系统设计与实现[J]. 小型微型计算机系统, 2006, 27(4): 720-723. (Zhang Liang, Feng Chong, Chen Zhaoxiong, et al. Design and Implementation of FAQ Automatic Answering System Based on Similarity Computing [J]. Journal of Chinese Computer Systems, 2006, 27(4): 720-723.)
[12] 吴鹏, 王曰芬, 丁晟春, 等. 基于本体的机械产品设计知识表示研究[J]. 情报理论与实践, 2013, 36(10): 91-95. (Wu Peng, Wang Yuefen, Ding Shengchun, et al. Research of Machine Product Design Knowledge Presentation Based on Ontology [J]. Information Studies: Theory & Application, 2013, 36(10): 91-95.)
[13] 张宇, 刘挺, 文勖. 基于改进贝叶斯模型的问题分类[J]. 中文信息学报, 2005, 19(2): 100-105. (Zhang Yu, Liu Ting, Wen Xu. Modified Bayesian Model Based Question Classification[J]. Journal of Chinese Information Processing, 2005, 19(2): 100-105.)
[14] 覃世安, 李法运. 文本分类中TF-IDF方法的改进研究[J]. 现代图书情报技术, 2013(10): 27-30. (Qin Shian, Li Fayun. Improved TF-IDF Method in Text Classification [J]. New Technology of Library and Information Service, 2013(10): 27-30.)
[15] 张华平, 刘群. 基于角色标注的中国人名自动识别研究[J]. 计算机学报, 2004, 27(1): 85-91. (Zhang Huaping, Liu Qun. Automatic Recognition of Chinese Personal Name Based on Role Tagging [J]. Chinese Journal of Computers, 2004, 27(1): 85-91.)
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