A Hyperlipemia Information Analysis System based on immune algorithm

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 we...

Full description

Saved in:
Bibliographic Details
Main Authors: Qirui Zhang, Man Luo, Hexian Wang, Jinghua Tan
Format: Conference Proceeding
Language:English
Subjects:
Analytical models
Computational modeling
document indexing
Hyperlipemia
immune algorithm
information analysis
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2161-9069
DOI:10.1109/ICCASM.2010.5620593