Web Page Rank Prediction with Markov Models

摘要：

In this paper we propose a method for predicting the ranking position of a Web page. Assuming a set of successive past top-k rankings, we study the evolution of Web pages in terms of ranking trend sequences used for Markov Models training, which are in turn used to predict future rankings. The predictions are highly accurate for all experimental setups and similarity measures.

关键词： Ranking prediction Markov Models

作者: Michalis Vazirgiannis Dimitris Drosos Pierre Senellart Akrivi Vlachou

作者单位: INRIA Futurs Orsay, France Athens Univ. of Economics & Business Athens, Greece INRIA Futurs & Univ. Paris-Sud Orsay, France

会议类型: 国际会议

会议名称: 第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-04-21（万方平台首次上网日期，不代表论文的发表时间）