Title :
Community Discovery of P2P Resources Based on Bipartite Graph
Author :
Li Jin ; Zhou Zhu-rong
Author_Institution :
Coll. of Comput. & Inf. Sci., Southwest Univ., Chongqing, China
Abstract :
Finding related resources is important for assisting resource retrieval and recommendation in the P2P network. This paper proposes a method for discovering such clusters of related resources, which are called resource communities. Graph mining approach is applicable here. Discovering communities is based on bipartite graph which is composed of resources and keywords. The data is extracted from the analysis of users´ search and download behavior. Experiment shows that this method is effective in discovering resource communities and improving the efficiency of resource retrieval.
Keywords :
data mining; graph theory; information retrieval; peer-to-peer computing; P2P resources; bipartite graph; community discovery; graph mining approach; resource communities; resource recommendation; resource retrieval; Bipartite graph; Computer networks; Costs; Data mining; Educational institutions; Humans; Information retrieval; Information science; Optimization methods; Peer to peer computing;
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
DOI :
10.1109/CISE.2009.5365800
