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Research on Personalized Services of Library Based on User Behavior Modeling and Big Data Mining
Received date: 2016-09-19
Revised date: 2016-11-10
Online published: 2017-01-05
[Purpose/significance] It is an urgent problem for libraries big data application to model user behaviors and provide personalized services based on amass data of user logs under big data background.[Method/process] Firstly, the research status and current dilemma of user behavior model is analyzed, then considering the characteristic of personalized services under big data background, the modeling strategy and method for library user behavior are put forward based on ontology technology, and a personalized service scheme is proposed after the ontology words of user explicit interests and implicit requirements have been extracted from user logs database, and finally an application case for library personalized services is provided based on Hadoop platform and MapReduce framework.[Result/conclusion] The proposed user behavior ontology model can be seamlessly combined with analysis platform of big data, providing personalized services timely and precisely, and responding the challenges of current library personalized services such as "knowledge loss","Information overload" and " emotional deficit" under big data background.
Key words： user behavior model; personalized service; ontology; big data; linked open data
He Sheng , Feng Xinling , Wu Qunhui , Xiong Taichun , Li Renpu . Research on Personalized Services of Library Based on User Behavior Modeling and Big Data Mining[J]. Library and Information Service, 2017 , 61(1) : 40 -46 . DOI: 10.13266/j.issn.0252-3116.2017.01.005
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