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装备采办知识搜索引擎关键技术研究

Research on the Key Technology of Equipment Procurement Knowledge Searching Engine
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摘要 研究并设计了装备采办知识搜索引擎系统结构,包括搜索模块、索引模块、检索模块、查询扩展模块和结果聚类模块。就装备采办知识管理搜索关键技术查询扩展模块和结果聚类模块,提出了相似性度量的渐进直推式支持向量机(similarity measurement progressive tranductive support vector machine,SMPTSVM)查询扩展模型,以及基于人工免疫算法的搜索引擎结果聚类算法。实验结果表明,该模型和算法提高了搜索结果的查全率、查准率及搜索结果的平均聚类精度。 This paper researches and designs the equipment procurement knowledge searching en-gine system structure .The system structure has five modules ,including scouting module ,indexing module ,searching module ,inquiring extension module and clustering module .About extend module and clustering module ,it proposes similarity measurement progressive tranductive support vector ma-chine (SMPTSVM) inquiring extension model and search engine results clustering algorithm based on artificial immune algorithm .The experimental results show that this method can improve the recall ratio ,precision and the average clustering precision of the search results .
出处 《装备学院学报》 2014年第2期90-93,共4页 Journal of Equipment Academy
基金 部委级资助项目
关键词 装备采办 查询扩展 支持向量机 聚类 equipment procurement inquiring extension support vector machine clustering
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  • 1Liu H, Huang S T. Fuzzy Transductive Support Vector Machines for Hypertext Classification. International Journal of Uncertainty, Fuzziness Knowledge-Based Systems, 2004, 12 ( 1 ) : 21 - 36.
  • 2Vapnik V N. The Natural of Statistical Learning Theory. New York, USA : Springer-Verlag, 1995.
  • 3Joachims T. Transductive Inference for Text Classification Using Support Vector Machines// Proc of the 16th International Conference on Machine Learning. Bled, Slovenia, 1999 : 200 - 209.
  • 4Chapelle O, Chi M, Zien A. A Continuation Method for Semi-Supervised SVMs// Proc of the 23rd International Conference on Machine Learning. Pittsburgh, USA, 2006: 185-192.
  • 5Astorino A, Fuduli A. Nonsmooth Optimization Techniques for Semi-Supervised Classification. IEEE Trans on Pattern Analysis and Machine Intelligence, 2007, 29(12): 2135-2142.
  • 6Tian Yingjie, Yan Manfu. Unconstrained Transduetive Support Vector Machines// Proc of the 4th Intemational Conference on Fuzzy System Knowledge Discovery. Haikou, China, 2007, Ⅱ: 181 - 185.
  • 7Silva M M, Maia T T, Braga A P. An Evolutionary Approach to Transduction in Support Vector Machines//Proc of the 5th International Conference on Hybrid Intelligence System. Kitakyushu, Japan, 2005 : 329 -334.
  • 8Sun Fun, Sun Maosong. A New Transductive Support Vector Machine Approach to Text Categorization//Proe of the IEEE International Conference on Natural Language Processing and Knowledge Engineering. Beijing, China, 2005 : 631 -635.
  • 9Chen Yisong, Wang Guoping, Dong Shihai. Learning with Progressive Transductive Support Vector Machine. Pattern Recognition Letters, 2003, 24(6) : 1845 - 1855.
  • 10Bruzzone L, Chi M, Marconcini M. A Novel Transduetive SVM for Semisupervised Classification of Remote-Sensing Images. IEEE Trans on Geoscience and Remote Sensing, 2006, 44( 11 ) : 3363 - 3373.

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