On filtering irrelevant results in peer-to-peer search

Authors:
Yuval Merhav;Ophir Frieder
Affiliations:
Illinois Institute of Technology;Georgetown University and IIT Information Retrieval Laboratory
Venue:
Proceedings of the 2008 ACM symposium on Applied computing
Year:
2008

Citing 2
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Abstract

To improve Peer-to-Peer (P2P) search accuracy, we identify multiword entities in user queries using an entity corpus constructed based on n-gram statistics collected from LimeWire users. We show that by using a statistical function, we can build a reliable corpus and successfully parse each user query to its correct entities. Our hypothesis: With entity matching, overall precision can be significantly improved, while only slightly decreasing recall.