摘要
针对当前高校学科信息服务平台存在的对服务对象信息需求挖掘、分析不足的弊端,提出构建基于协同过滤算法的学科信息服务平台。通过引入读者专业、角色、学历、借阅记录等影响和反映读者信息需求的因素构建读者特征模型,该模型采用优化的协同过滤算法挖掘读者信息需求并产生个性化推荐信息,可有效提升学科信息服务质量。
In view of the fact that the current university subject information service platform has the disadvantages of insufficient mining and analysis of the reader＇s information demand,this paper proposes to construct a subject information service platform based on collaborative filtering algorithm.The paper constructs a reader characteristic model by introducing the factors such as the reader＇s speciality,role,educational background and borrowing records that influence and reflect the reader＇s information demand.The model uses the optimized collaborative filtering algorithm to mine the reader＇s information demand and provide personalized information recommendation,which can improve the quality of subject information service effectively.
出处
《情报理论与实践》
CSSCI
北大核心
2012年第5期77-80,共4页
Information Studies:Theory & Application
基金
中南民族大学中央高校基本科研业务费专项资金项目"图书馆个性化信息服务体系研究"的成果之一
项目编号:CZQ10008
关键词
协同过滤
学科信息服务平台
数据挖掘
构建
collaborative filtering
subject information service platform
data mining
construction
