计算机工程

• 先进计算与数据处理 • 上一篇    下一篇

基于语义的医疗资源均衡推荐算法

徐守坤,吴伟伟   

  1. (常州大学信息科学与工程学院,江苏 常州 213164)
  • 收稿日期:2014-08-26 出版日期:2015-09-15 发布日期:2015-09-15
  • 作者简介:徐守坤(1972-),男,教授、博士、CCF会员,主研方向:数据库技术,信息系统,普适计算;吴伟伟,硕士研究生。
  • 基金项目:
    江苏省产学研前瞻性联合研究基金资助项目“医疗信息个性化推荐技术及应用研究”(BY2013024-06)。

Balance Recommendation Algorthm for Medical Resources Based on Semantic

XU Shoukun,WU Weiwei   

  1. (School of Information Science & Engineering,Changzhou University,Changzhou 213164,China)
  • Received:2014-08-26 Online:2015-09-15 Published:2015-09-15

摘要: 传统医疗资源推荐算法中用户面临资源选择信息过载的问题,为此,从用户和医生2个角度出发,提出一种基于语义的医疗资源均衡推荐算法。采用语义本体技术对医疗资源与用户进行建模,给出一种机器能够理解的标准信息表示方法。融入稳定匹配算法处理推荐过程中的个性化匹配,同时加入推理规则进行匹配筛选,使个性化推荐中用户的个性特征与医生资源具体属性相匹配。理论分析和实验结果表明,该推荐算法能够降低用户选择医疗资源时的负担,提高用户的需求满意度和系统的推荐质量。

关键词: 医疗资源, 偏好, 语义, 本体, 稳定匹配, 推理规则

Abstract: The traditional algorithms for source options have the shortcoming of the information overload.In this paper,a stable matching algorithm is proposed based on the semantic from the aspects of user and doctor.This algorithm adopts the technology of the semantic ontology by which the medical resources and users are modeled.And it provides a standard information method which the machine can understand.The algorithm uses the inference rules to matching filter.It also solves the specific properties of matching between personality characteristics of users and doctors resources in personalized recommendation.Theoretical analysis and experiments results show that the recommended method can reduce the burden of users who select medical resources.It also improves the quality of users’ needs and system’s recommendation quality.

Key words: medical resource, preference, semantic, ontology, stable matching, inference rules

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