Blog distillation using random walks

Mostafa Keikha, Mark James Carman, Fabio Crestani
2009 Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '09  
This paper addresses the blog distillation problem. That is, given a user query find the blogs most related to the query topic. We model the blogosphere as a single graph that includes extra information besides the content of the posts. By performing a random walk on this graph we extract most relevant blogs for each query. Our experiments on the TREC'07 data set show 15% improvement in MAP and 8% improvement in Precision@10 over the Language Modeling baseline.
doi:10.1145/1571941.1572054 dblp:conf/sigir/KeikhaCC09 fatcat:hbgq4tlerngppnqwzgeabuhg44