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Deep Mining and Explore of User Intelligence Demand under the Environment of the Intention Economy
Received date: 2016-06-27
Revised date: 2016-11-28
Online published: 2017-01-05
[Purpose/significance] The intention economy is a kind of new economic pattern which is formed around the users' intention and demand-oriented with the development of Internet and big data technology.In this mode of economic behavior, the research on deepmining of user intelligence demandis of great significance to enhance the intelligence service.[Method/process] This paper takes intelligence service revolution under the environment of intention economy as the breakthrough point,andputs forward the research of user intelligence demand. Itbuilds the UDAM (User Demand Analysis Model) to describeintelligencedemand of new and old users on the intelligence service platform. It uses the text feature vector analysis method to learn intelligence reports, which users bought from intelligence service platform. The key words and user's interests changing of intelligence demand in time are found out, anduser's intelligence demandaredeeplymined and dynamiclyscouted.[Result/conclusion] Under the thinking patterns of intention economy, supplying intelligence initiative push service to users, which can meet user demand for the purpose of personalized, is the inevitable trend of future intelligence service development.
Liu Ru , Li Menghui , Zhang Huina , Huang Yurong , Zhou Jingyan . Deep Mining and Explore of User Intelligence Demand under the Environment of the Intention Economy[J]. Library and Information Service, 2017 , 61(1) : 14 -24 . DOI: 10.13266/j.issn.0252-3116.2017.01.002
[1] SEARLS D. The intention economy:when customers take charge[M]. Massachusetts:Harvard Business Review Press, 2012.
[2] HarvardUniversity.R-button in vendor relationship management[EB/OL].[2016-09-25]. https://cyber.harvard.edu/projectvrm/R-button.
[3] 靖继鹏,马费成,张向先.情报科学理论[M].北京:科学出版社,2009.
[4] 王秀成.论情报科学研究中的带头领域[J].情报科学,1990(4):27-30.
[5] 靖继鹏,李勇先.试构造以用户为核心的情报学理论体系[J].情报业务研究,1991(4):193-198.
[6] 曹磊,陈灿,郭勤贵,等.互联网+跨界与融合[M].北京:机械工业出版社,2015.
[7] 茵沫.意愿经济重构消费者主权[J].互联网周刊,2016(5):24.
[8] 郑荣,杨冉.基于云服务平台的竞争情报服务联盟构建研究[J].情报理论与实践,2016(39):55-56.
[9] 余晖.半官方教育智库如何服务政府决策——香港教育统筹委员会的经验与启示[J].现代教育管理,2015(12):17-22.
[10] 张硕.中小企业竞争情报服务中的用户模型研究[D].大连:大连理工大学,2010.
[11] 潘建国.基于语义的用户建模技术与应用研究[D]. 上海:上海大学计算机工程与科学学院,2008.
[12] LATAPY M,MAGNIEN C,VECCHIO N D. Basic notions for the analysis of large two-mode networks[J].Social networks, 2008,30(1):31-48.
[13] DEERWESTER S, DUMAIS S T, FURNAS G W, et al.Indexing by latent semantic analysis[J]. Journal of the American Society for Information Science and Technology, 1990,41(10):391-407.
[14] JOACHIM T.Text categorization with support vector machines:learning with many relevant features[J]. European conference on machine learning, 1998,10 (1):137-142.
[15] 蒲雷.组织决策情报需求分析方法研究[J]. 现代情报, 2009, 29(8):48-50.
[16] 王庆红,王平.企业用户情报需求挖掘及资源关联可视化展示研究[J]. 图书与情报,2014(3):27-32.
[17] 陶秀杰, 龚婷, 吴志强. 基于交互式情报用户需求深度挖掘的电网信息检索方法研究[J]. 图书情报知识, 2014(4):57-62.
[18] 涂海丽,唐晓波,谢力.基于在线评论的用户需求挖掘模型研究[J]. 情报学报, 2015(10):88-97.
[19] 卢扬竹,张新有,祁玉. 邮件过滤中特征选择算法的研究及改进[J]. 计算机应用, 2009, 29(10):2812-2815.
[20] 吴晓平,张长利,朱丽娜. 基于网页内容块策略的主题爬行[J].计算机工程与应用, 2008, 44(9):143-146.
[21] 张琼.Web主题网页内容安全监管研究[D].西安:西安电子科技大学,2008.
[22] 唐坚刚, 魏然. 基于权重均值的不良网页过滤算法研究[J]. 计算机工程与设计,2008, 29(5):1088-1089, 1107.
[23] RICCIL F,ROKACH L,SHAPIRA B,et al.Recommender systems handbook[M].Berlin:Springer. 2011.
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