基于可信度模型的HITS算法的改进

HITS是一种经典的Web链接分析算法,其主要问题是容易发生主题漂移和互相加强.针对这些问题,提出了一种改进的算法T-HITS.通过一种网络结构图来映射垃圾链接集与其对应的网站,并结合链接文本将垃圾链接排除,最后利用可信度模型来修正结果,实验数据表明改进后的算法提高了查询结果的相关度,减少了主题漂移的发生.

Improvements of the HITS algorithm based on the Model of credibility

HITS is one of the classical web link analysis algorithms, the main problem of it is the topic drift and mutual reinforcement. According to these problems, we propose an improved algorithm T-HITS, using a network structure to map spam collection with corresponding website and exclude the spam links with link text. At last we use the model of credibility to fix the results, and the experimental data shows that the improved algorithm has a big improvement about the degree of correlation of the results, and can decreases the probability of the topic drift.