TS-PageRank Algorithm Based on the Model of Topic Similarity
Neng Qian · Journal of Chinese Computer Systems · 2007
The PageRank algorithm is a key algorithm used in famous search engine Google,but there exists a bad problem of topic-drift,which results in too many web pages without any correlation with the user's search topic in the list of web pages searched by the algorithm. After analysing the PageRank algorithm and its modified algorithm,a similarity model based on virtual file vector and similar degree of cosine,and put forward a TS-PageRank algorithm frame.We can get many different TS-PageRank algorithms and form a set of TS-PageRank algorithm,if we use different similarity model in the frame. The analysis of theory and numerical simulation illustrate that the TS-PageRank algorithm can avoid the problem of topic-drift and improve the quanlity of web search effectively without adding any other extra text information or increasing the degree of time and space complexity.