Research on text mining algorithm based on focused crawler

Qiusheng Zhang, M. Lin, J. Jun, Xingyun Zhang
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引用次数: 2

Abstract

Internet has become the world's largest information repository, especially the explosive growth of the text data on the web, the disadvantages that it need much more time to acquire and update web pages, and is not high precision have become more obvious. The text mining algorithm based on focused crawler is proposed in this paper, it classifies and integrates the whole web pages by topic using topic crawler algorithm as much as possible, which greatly improves the retrieval ability of the web pages, naive bayes algorithm is adopted on this basis, which realizes the text mining processing of the web data. The experimental results show that the algorithm has good feasibility and higher recall ratio and precision ratio of the web pages.
基于聚焦爬虫的文本挖掘算法研究
互联网已经成为世界上最大的信息库,尤其是网络上文本数据的爆炸式增长,使得获取和更新网页需要更多的时间,而且精度不高的缺点更加明显。本文提出了基于焦点爬虫的文本挖掘算法,尽可能利用主题爬虫算法对整个网页按主题进行分类和整合,极大地提高了网页的检索能力,在此基础上采用朴素贝叶斯算法,实现了对网页数据的文本挖掘处理。实验结果表明,该算法具有较好的可行性,具有较高的网页查全率和查准率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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