Web page rank prediction with markov models

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. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications Data Mining General Terms Algorithms, Experimentation, Measurement Keywords Ranking prediction, Markov Models

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Michalis Vazirgiannis, Dimitris Drosos, Pierre Senellart, Akrivi Vlachou
• Keywords: Internet Technology, Keywords Ranking Prediction, Markov Models Training, Ranking Trend Sequences, WWW 2008