摘要
针对移动环境下读者个性化阅读需求具有高度的情境敏感性,本文面向数字图书馆领域提出一种基于情境感知的个性化信息推荐模型。首先,提出＂情境熵＂来度量读者对不同情境属性的情境感知度,并计算出每个情境属性在信息推荐中的相应权重值;在此基础上结合传统的协同过滤技术,提出一种基于情境感知的信息协同过滤推荐方法。实验验证了提出方法的有效性,能够较好地预测读者对情境属性的感知能力,为读者提供移动环境下个性化的阅读推荐服务。
Aiming at the high context-sensitive characteristics of readers＇ personalized reading needs in the mobile environment,this paper proposes a context-aware personalized recommendation model for the field of digital library.First,context entropy is proposed to measure readers＇ context perception on differ ent context attributes,and compute the corresponding weights of each context attributes in the process of recommendation.Based on it,combining the traditional collaborative filtering（CF）,a context-aware col laborative filtering recommendation approach is proposed.An experiment is conducted to verify the effec tiveness of the proposed approach,which can predict readers＇ context perception accurately,and thus pro vide personalized reading recommendation services for readers in the mobile environment.
出处
《情报科学》
CSSCI
北大核心
2013年第10期131-138,共8页
Information Science
基金
国家自然科学项目（71103136）
教育部人文社会科学重点研究基地重大项目（11JJD630001）
关键词
情境感知
数字图书馆
信息推荐
移动环境
context-aware
digital library
information recommendation
mobile environment
