ISSN : 1796-2048
Volume : 1    Issue : 6    Date : September 2006

P2P Content Searching Method using Semantic Vector which is Managed on CAN Topoogy
Yoji Yamato and Hiroshi Sunaga
Page(s): 1-9
Full Text:
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With today's advances in Peer-to-Peer (P2P) searching technology, a lot of non-document content
has become searchable and usable. In the near future, since a huge amount of content is
distributed over the networks, not only index server searching but also P2P searching will become
important because of its scalability and robustness. Typical P2P contents sharing services have
some problems, such as low search precision ratio, significant increase in traffic and inundations
of malicious content such as virus. In this paper, with ideas of the CAN (Content Addressable
Network) topology and a vector space method where vectors have a variable length, we propose a
new P2P content searching method in which a query is effectively forwarded only to peers that have
indices of content semantically similar to the desired one but not forwarded to the same peer
repeatedly. The main part of our proposal is to map non-document content to a vector space based
on users' evaluation and to manage vector space or to route queries using the CAN topology
control. The effectiveness of the proposal is shown both by analytical estimations and simulation
experiments. Our simulation experiments clarify that the proposed method is effective in improving
the precision and recall ratios while reducing the amount of traffic compared with the Gnutella
flooding and the vector space method in which vector lengths are fixed (close to pSearch method).
In particular, when there is a lot of malicious content, the proposed method exhibited a higher
precision ratio than other methods.

Index Terms
Peer-to-Peer, Content Retrieval, Vector Space Method, CAN, Semantic Vector