Automatic Community Discovery in Peer-to-Peer Systems
Weidong Gu, Wei Wei
Abstract
Weidong Gu, Wei Wei
Abstract
In many applications of peer-to-peer networks, such as information sharing and media streaming, a peer is much more likely to communicate with other peers with similar interests. Therefore, to optimize the structure of these systems, a good strategy is to form communities composed of peers with similar interests. In this paper, we propose a method to automatically identify a user's interests, and a distributed algorithm to discover communities based on the interests identified. We provide empirical results to demonstrate the correctness and efficiency of our algorithm
OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In many applications of peer-to-peer networks, such as information sharing and media streaming, a peer is much more likely to communicate with other peers with similar interests. Therefore, to optimize the structure of these systems, a good strategy is to form communities composed of peers with similar interests. In this paper, we propose a method to automatically identify a user's interests, and a distributed algorithm to discover communities based on the interests identified. We provide empirical results to demonstrate the correctness and efficiency of our algorithm
Key concepts: Computer science, Correctness, Peer-to-peer, Information sharing, Empirical research, World Wide Web, Distributed computing, Theoretical computer science