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模糊规则算法在教育信息分类中的应用
引用本文:梁文超,徐朝军,沈书生.模糊规则算法在教育信息分类中的应用[J].现代图书情报技术,2011,27(1):94-98.
作者姓名:梁文超  徐朝军  沈书生
作者单位:南京师范大学教育技术系 南京 210097
基金项目:本文系全国教育科学“十一五”规划2009年度教育部青年专项课题“网络课程使用现状自动量化评价系统研究”(项目编号:ECA090441)的研究成果之一。
摘    要:以中小学简介信息分类为例,在分析该类数据特征项少、权重不均等特点的基础上,采用去噪处理、基于模糊集的同义处理等策略构建类别特征库,并以特征库为依据,使用模糊规则构建分类模型,实现对短文本数据的分类。实验结果表明:对于类别特征项较少、权值分布不均的短文本分类,模糊规则分类优于VSM、Rocchio等分类算法。

关 键 词:TF-IDF  模糊规则  分类
收稿时间:2010-11-17
修稿时间:2010-12-17

Application of the Fuzzy Rule Algorithm in the Classification of Educational Information
Liang Wenchao Xu Chaojun Shen Shusheng.Application of the Fuzzy Rule Algorithm in the Classification of Educational Information[J].New Technology of Library and Information Service,2011,27(1):94-98.
Authors:Liang Wenchao Xu Chaojun Shen Shusheng
Institution:Department of Educational Technology, Nanjing Normal University, Nanjing 210097, China
Abstract:Because of the fact that the introductions of primary and secondary schools have less feature items and unequal weights, the authors use the strategies of denoising, processing synonym features based on fuzzy set to build category vocabularies, and then classify short texts using the classification model which is based on category vocabularies and fuzzy rules. The results show that using fuzzy rules to classify the short texts which have less feature items and uneven distribution of weight is better than VSM, Rocchio and other classification algorithms.
Keywords:TF-IDF  Fuzzy rules  Classification
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