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.%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。
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