Web文本挖掘中的特征选取方法研究

Study on Feature Selection Algorithms in Web Text Mining

研究了Web文本挖掘中的高维特征选取问题,对常见的评估函数法、主成分分析法、模拟退火法等特征选取和降维算法进行了理论分析与性能比较,通过实验对各种算法的优劣性及适用性进行了讨论。旨在通过降维处理来解决高维空间的文本挖掘问题。

Feature selection is the key technology in the text mining field. This paper studies the feature selection algorithms, discusses some familiar algorithms such as evaluation function, principle component analysis and simulating anneal. With the experiment analysis, it compares the capability, the advantage and the limitation of these algorithms.