SETS: search enhanced by topic segmentation

We present SETS, an architecture for efficient search in peer-to-peer networks, building upon ideas drawn from machine learning and social network theory. The key idea is to arrange participating sites in a topic-segmented overlay topology in which most connections are short-distance, connecting pairs of sites with similar content. Topically focused sets of sites are then joined together into a single network by long-distance links. Queries are matched and routed to only the topically closest regions. We discuss a variety of design issues and tradeoffs that an implementor of SETS would face. We show that SETS is efficient in network traffic and query processing load. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Clustering, Search process, Selection process; H.3.4 [Systems and Software]: Distributed Systems, Performance Evaluation (efficiency and effectiveness) General Terms Algorithms, Performance, Design Keywords Peer-to-Peer (P2P), distributed infor...

• Type: Conference
• Year: 2003
• Where: SIGIR
• Authors: Mayank Bawa, Gurmeet Singh Manku, Prabhakar Raghavan
• Keywords: Peer-to-peer Networks, SIGIR 2003, Social Network Theory, Topic-segmented Overlay Topology