制造业大数据联盟资源推送服务算法
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摘要
为了提高制造业大数据联盟资源共享效果及联盟成员的满意度,提出一种基于互信息特征权重和相似度的制造业大数据联盟资源推送算法。利用互信息特征权重和特征相似度分别对制造业大数据联盟成员评分和最近邻居产生的评分加以改进,从而提高资源推送质量。实验结果表明,该算法在一定程度上解决了制造业大数据联盟新成员资源推送和数据稀疏问题,有效提高了制造业大数据联盟成员满意度。
To enhance the efficiency of data sharing and the satisfaction of big data alliance members in manufacturing industry,a resource pushing algorithm based on mutual information feature weight and similarity was proposed.To improve the quality of resource push,the scores of big data alliance members and the nearest neighbors were improved by using mutual information feature weight and feature similarity.The results showed that the algorithm could solve the problem of data push and data sparsity of alliance new members to a certain extent,and improve the satisfaction of big data alliance members effectively.
To enhance the efficiency of data sharing and the satisfaction of big data alliance members in manufacturing industry,a resource pushing algorithm based on mutual information feature weight and similarity was proposed.To improve the quality of resource push,the scores of big data alliance members and the nearest neighbors were improved by using mutual information feature weight and feature similarity.The results showed that the algorithm could solve the problem of data push and data sparsity of alliance new members to a certain extent,and improve the satisfaction of big data alliance members effectively.
引文
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[23]YANG Yang,XIANG Yang,XIONG Lei.Collaborative filtering and recommendation algorithm based onmatrix factorization and user nearest neighbor model[J].Journal of Computer Applications,2012,32(2):395-398(in Chinese).[杨阳,向阳,熊磊.基于矩阵分解与用户近邻模型的协同过滤推送算法[J].计算机应用,2012,32(2):395-398.]
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[26]GAO Peng.Research on information similarity in recommender systems and its applications[D].Shanghai:Shanghai Jiao Tong University,2012:33-35(in Chinese).[高鹏.推荐系统中信息相似度的研究及其应用[D].上海:上海交通大学,2012:33-35.]
[27]CIHAN K.An entropy-based neighbor selection approach for collaborative filtering[J].Knowledge-Based Systems,2013,11(20):56-65.
[28]PIAO C H,ZHAO J,ZHANG L J.Research on entropybased collaborative filtering algorithm and personalized recommendation in e-commerce[J].Service Oriented Computing and Applications,2009,3(2):147-157.
[29]ZHAO Zheng,WANG Lei,LIU Huan.On similarity preserving feature selection[J].IEEE Transactions on Knowledge and Data Engineering,2013,25(3):619-632.
[30]ZHU Yuxiao,LYU Linyuan.Evaluation metrics for pecommender systems[J].Journal of University of Electronic Science and Technology of China,2012,41(2):164-174(in Chinese).[朱郁筱,吕琳媛.推送系统评价指标综述[J].电子科技大学学报,2012,41(2):164-174.]
[31]GUO Lei,MA Jun,CHEN Zhumin.Incorporating item relations for social recommendation[J].Chinese Journal of Computers,2014,37(1):223-227(in Chinese).[郭磊,马军,陈竹敏.一种结合推送对象间关联关系的社会化推送算法[J].计算机学报,2014,37(1):223-227.]
[32]MANNING C,RAGHAVAN P,SCHUTZE H.Introduction to information retrieval[M].Cambridge,UK:Cambridge University Press,2008.
[2]YAO Xifan,YU Miao,CHEN Yong,et al.Internet of manufacturing things:connotation,architecture and key technologies[J].Computer Integrated Manufacturing Systems,2014,20(1):1-10(in Chinese).[姚锡凡,于淼,陈勇,等.制造物联的内涵、体系结构和关键技术[J].计算机集成制造系统,2014,20(1):1-10.]
[3]DAVIS J,EDGAR T,POTER J,et al.Smart manufacturing,manufacturing intelligence and demand-dynamic performance[J].Computers&Chemical Engineering,2012,47(12):145-156.
[4]YAO Xifan,ZHOU Jiajun,ZHANG Cunji,et al.Proactive manufacturing-a big data driven emerging manufacturing paradigm[J].Computer Integrated Manufacturing Systems,2017,23(1):172-185(in Chinese).[姚锡凡,周佳军,张存吉,等.主动制造——大数据驱动的新兴制造范式[J].计算机集成制造系统,2017,23(1):172-185.]
[5]WILSCHUT T,ADAN B F,STOKKERMANS J.Big data in daily manufacturing operations[C]//Proceedings of 2014 Winter Simulation Conference.Washington,D.C.,USA:IEEE,2014:2364-2375.
[6]SHARMA A B,IVANCIC F,ALEXANDRU N A.Modeling and analytics for cyber-physical systems in the age of big data[J].Performance Evaluation Review,2014,41(4):74-77.
[7]MOYNE J,SAMANTARAY J,ARMACOST M.Big data emergence in semiconductor Manufacturing advanced process control[C]//Proceedings of Conference on the 2015 26th Annual SEMI Advanced Semiconductor manufacturing.Washington,D.C.,USA:IEEE,2015:130-135.
[8]COURTNEY B.Industrial big data analytics:the present and future[J].In Tech Magazine,2014,61(4):12-14.
[9]JIAO Yuying,SUO Chuanjun.Network service mechanism based on the“push”model and related technologies[J].Journal of the China Society for Scientific and Technical Information,2001,20(2):193-199(in Chinese).[焦玉英,索传军.基于“推”模式的网络信息服务及其相关技术研究[J].情报学报,2001,20(2):193-199.]
[10]ZHENG Libin,CHEN Quanyuan,GU Jinan.The research on personalized active pushing of manufacturing resources[J].Machine Design and Research,2015,31(6):77-80(in Chinese).[郑立斌,陈全园,顾寄南.制造资源个性化推送服务研究[J].机械设计与研究,2015,31(6):77-80.]
[11]FANG Hui,TAN Jianrong,TAN Ying.Manufacturing information active recommendation based on Web services[J].Computer Integrated Manufacturing Systems,2008,14(11):2253-2260(in Chinese).[方辉,谭建荣,谭颖.基于Web的制造信息主动推荐服务研究[J].计算机集成制造系统,2008,14(11):2253-2260.]
[12]CAO Zhimei.Research on personalized information service mode of Library[J].Journal of Library Science in China,2006,32(2):79-81(in Chinese).[曹志梅.图书馆个性化信息服务模式研究[J].中国图书馆学报,2006,32(2):79-81.]
[13]TAO Li.Analysis and research of library personalized information service[J].Journal of Library Science,2005,27(4):92-93(in Chinese).[陶力.图书馆个性化信息服务分析与研究[J].图书馆学刊,2005,27(4):92-93.]
[14]LOU Hongqing.Personalized information services with network in libraries[J].Library Tribune,2004,24(6):195-199(in Chinese).[楼宏青.网络环境下的图书馆个性化信息服务[J].图书馆论坛,2004,24(6):195-199.]
[15]LIAO I E,WEN C H,CHENG M S.A library recommender system based on a personal ontology model and collaborative filtering technique for English collections[J].The Electronic Library,2010,28(3):386-400.
[16]LEKAKOS G,CARAVELAS P.A hybrid approach for movie recommendation[J].Multimedia Tools and Applications,2008,36(1/2):55-70.
[17]ZHU Lizhong,XU Xiujuan,LIU Yu.Collaborative Filtering recommendation algorithm based on item and trust[J].Computer Engineering,2013,39(1):58-62(in Chinese).[朱丽中,徐秀娟,刘宇.基于项目和信任的协同过滤推荐算法[J].计算机工程,2013,39(1):58-62.]
[18]LIU Weining,LIU Bo,SUN Dihua.Muli-task oriented service composition in cloud manufacturing[J].Computer Integrated Manufacturing Systems,2013,19(1):200-208(in Chinese).[刘卫宁,刘波,孙棣华.面向多任务的制造云服务组合[J].计算机集成制造系统,2013,19(1):200-208.]
[19]ZHAO Guangyan,LI Yusheng,HAN Hao.Collaborative filtering algorithm based onco-clustering and matrix decomposition[J].Journal of Wuhan Polytechnic University,2014,33(2):61-62(in Chinese).[赵广艳,李禹生,韩昊.基于联合聚类和矩阵分解的协同过滤算法[J].武汉轻工大学学报,2014,33(2):61-62.]
[20]TU Dandan,SHU Chengchun,YU Haiyan.Using unified probabilistic matrix factorization for contextual advertisement recommendation[J].Journal of Software,2013,24(3):454-464(in Chinese).[涂丹丹,舒承椿,余海燕.基于联合概率矩阵分解的上下文广告推送算法[J].软件学报,2013,24(3):444-464.]
[21]LI Gai,LI Lei.A new algorithm of cold-start in a collaborative filtering system[J].Journal of Shandong University:Engineering Science,2012,42(2):11-16(in Chinese).[李改,李磊.一种解决协同过滤系统冷启动问题的新算法[J].山东大学学报:工学版,2012,42(2):11-16.]
[22]LI Cong,LIANG Changyong.Cold-start eliminating method of collaborative filtering based on n-sequence access analytic logic[J].Systems Engineering—Theory&Practice,2012,32(7):1538-1543(in Chinese).[李聪,梁昌勇.基于n序访问解析逻辑的协同过滤冷启动消除方法[J].系统工程理论与实践,2012,32(7):1538-1543.]
[23]YANG Yang,XIANG Yang,XIONG Lei.Collaborative filtering and recommendation algorithm based onmatrix factorization and user nearest neighbor model[J].Journal of Computer Applications,2012,32(2):395-398(in Chinese).[杨阳,向阳,熊磊.基于矩阵分解与用户近邻模型的协同过滤推送算法[J].计算机应用,2012,32(2):395-398.]
[24]WEI Suyun,YE Ning,JI Genlin.Collaborative filtering recommendation algorithm based on item category and interest[J].Journal of Nanjing University:Natural Sciences,2013,49(2):17-24(in Chinese).[韦素云,业宁,吉根林.基于项目类别和兴趣度的协同过滤推送算法[J].南京大学学报:自然科学版,2013,49(2):17-24.]
[25]VINH L T,LEE S.A novel feature selection method based on normalized mutual information[J].Springer Science Business Media,2012,37(1):120-150.
[26]GAO Peng.Research on information similarity in recommender systems and its applications[D].Shanghai:Shanghai Jiao Tong University,2012:33-35(in Chinese).[高鹏.推荐系统中信息相似度的研究及其应用[D].上海:上海交通大学,2012:33-35.]
[27]CIHAN K.An entropy-based neighbor selection approach for collaborative filtering[J].Knowledge-Based Systems,2013,11(20):56-65.
[28]PIAO C H,ZHAO J,ZHANG L J.Research on entropybased collaborative filtering algorithm and personalized recommendation in e-commerce[J].Service Oriented Computing and Applications,2009,3(2):147-157.
[29]ZHAO Zheng,WANG Lei,LIU Huan.On similarity preserving feature selection[J].IEEE Transactions on Knowledge and Data Engineering,2013,25(3):619-632.
[30]ZHU Yuxiao,LYU Linyuan.Evaluation metrics for pecommender systems[J].Journal of University of Electronic Science and Technology of China,2012,41(2):164-174(in Chinese).[朱郁筱,吕琳媛.推送系统评价指标综述[J].电子科技大学学报,2012,41(2):164-174.]
[31]GUO Lei,MA Jun,CHEN Zhumin.Incorporating item relations for social recommendation[J].Chinese Journal of Computers,2014,37(1):223-227(in Chinese).[郭磊,马军,陈竹敏.一种结合推送对象间关联关系的社会化推送算法[J].计算机学报,2014,37(1):223-227.]
[32]MANNING C,RAGHAVAN P,SCHUTZE H.Introduction to information retrieval[M].Cambridge,UK:Cambridge University Press,2008.