Authors: Kei Ohnishi; Hiroshi Yamamoto
Addresses: Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan ' Ritsumeikan University, 1-1-1 Nojihigashi, Kusatsu, Shiga, 525-8577 Japan
Abstract: We propose a hybrid P2P information search system that combines: 1) the idea that a searcher searches not information itself but people who have KANSEI (human sensitivity) well fitted to the searcher; 2) a P2P network on which we can build a scalable information search system; 3) a folksonomy, which is a system that allows users to classify information by themselves, to quickly and reliably obtain the desired information from on the network. The main characteristic of the proposed system is that it produces a two-dimensional map visualising the KANSEI information of all nodes by a self-organising map, and then utilises the map for searches. The simulation results show that the proposed system provides balanced opportunities from which we obtain our desired information and other unknown information, in comparison with a search method that conducts searches directly in higher-dimensional space and a random search method.
Keywords: hybrid P2P networks; information search; visualisation; self-organising maps; SOM; Kansei information; peer-to-peer; node maps; folksonomy; simulation; information retrieval.
International Journal of Soft Computing and Networking, 2016 Vol.1 No.1, pp.82 - 110
Received: 19 Jan 2015
Accepted: 04 Jun 2015
Published online: 20 Jun 2016 *