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T o overcome the problem s o f data sparse and cold s ta rt based on trad itiona l co llaborative f i lte r in g a lg o rith m , when co llaborative f i lte r in g re la tionsh ip is established between commanders and command elem ents, a m ission-oriented m u lti-co llabo ra tive f i lte r in g a lg o rith m o f command in fo rm a tion was proposed. F irs t ly , the a lgo rith m perform s cloud model-based pro-co llabora tive f i lte r in g by operation type on the command elem ents, and then in tegrates the cohesion subset analysis in to user-based co llaborative f i lte r in g to m ine the s im ila rities between the commanders and command elements under specific operation types, thus to achieve accurate recommendations. T he experim ental resu lts show tha t the proposed a lg o rith m can be applied to the command in fo rm a tion system o f operational m ission effec tive ly and im ­ proves the recom m endation effic iency and accuracy o f the system.

基于云模型的指挥信息多重协同过滤算法研究 (Study on Multi-collaborative Filtering Algorithm of Command Information Based on Cloud Models).