A Hyperlipemia Information Analysis System Based on Immune Algorithm

摘要：

This paper designs a Hyperlipemia Information Analysis System, which can realize hyperlipemia document classification and information analysis. In document indexing, we propose an improved approach, called Term Frequency, Inverted Document Frequency and Inverted Entropy (TFIDFIE), to compute term weights in document indexing. In addition, an improved immune algorithm proposed by us is used in this system, which called Clonal Selection Algorithm Based on Antibody Density (CSABAD). According to the clonal selection principle and density control mechanism, only those cells that have higher affinity and lower density are selected to proliferate. The system obtains better classification performance. In further work, we will research the feature selection and data mining for hyperlipemia.

关键词： hyperlipemia information analysis immune algorithm document indexing

作者: Qirui Zhang Man Luo Hexian Wang Jinghua Tan

作者单位: Key Unit of Modulating Liver to Treat Hyperlipemia SATCM, Guangzhou, China College of Medical Inform Guangzhou Research and Development Center, China Telecom, Guangzhou, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 421-424

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）