NQPC:一种新型的基于查询日志的网页分类方法

NQPC:novel query log-based web-page classification method

网页分类可对海量网页进行分门别类,可应用于许多方面。现存的网页自动分类方法较多,其中常用的基于网页内容的方法由于网页内容的不纯,导致其存在较大的性能提升空间。基于查询日志,提出了一种新型的网页分类方法NQPC。该方法提出一种低维特征向量抽取方法,从而避免"维度灾难";基于优质的查询日志进行网页分类,查询日志相对网页内容而言,具有内容较纯的优点;提出一种提升分类准确率的过滤方法。实验结果表明,提出的网页分类方法具有优异的性能表现,使其具有良好的应用前景。

Web-page classification can be utilized to categorize massive web-pages and thus can be utilized in lots of areas.There are quite a few existing automatic web-page classification methods,among which there is large performance improvement space for the commonly-used web-content-based method,due to the impurity of page content.In this paper,based on query log,a novel web-page-classification method NQPC（Novel Query log-based web-Page Classification）is proposed.Its novelty is that： a low-dimensional feature vector extraction method is proposed to avoid the＂curse of dimensionality＂;web-page classification is based on high-quality query log,which has purer content than web-page content;a filter method is proposed to improve the classification accuracy.Experimental results show that the web-page-classification method has excellent performance,which gives it good application prospects.