Document re-ranking based on Markov network
Yin Cao · Journal of Chongqing University of Posts and Telecommunications · 2013
In information retrieval,search results re-ranking can improve retrieval system through internal document relation extracted from webpage link information.In this paper we propose a document re-ranking technique based on Markov network,which can explain the sematic relationship between documents better,and can be used to compute the document importance,which is combined with the initial search results into re-rank stage.First,we analyze the algorithm of constructing document Markov network,and then explain the scoring method of Top-k and its related documents,to revise the initial retrieval score.The experiment results on several different data sets demonstrate the effectiveness of the proposed document re-ranking method.Compared to the traditional PageRank method,it has stable advantage.