Filtering Spamming Pages Utilizing a Modified PageRank Algorithm

摘要

The World Wide Web has become an entrenched global medium for storing and searching information. Most people begin at a Web search engine to find information, but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a spamming page like Google bombing that is based on the PageRank algorithm, one of many Web structure mining techniques. In this paper, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web spamming pages effectively.