Self Recommendation in Peer to Peer Systems

Agostino Forestiero


Recommendation system aims to produce a set of significant and useful suggestions that can be meaningful for a particular user. This paper introduces a self-organizing algorithm that by exploiting of a decentralized strategy builds a distributed recommendation system. The available resources are represented by a string of bits namely describer. The describers are obtained by exploiting of a locality preserving hash function that maps similar resources into similar strings of bits. Each pear works independently with the aim to locate the similar describer in neighbor peers. The peer decisions are based on the application of ad-hoc probability functions. The outcome will be a fast recommendation service thanks to the emergent sorted overlay-network. Preliminaries experimental results show as the logical reorganization can improve the recommendation operations.


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Paper Citation

in Harvard Style

Forestiero A. (2014). Self Recommendation in Peer to Peer Systems . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014) ISBN 978-989-758-052-9, pages 332-336. DOI: 10.5220/0005157603320336

in Bibtex Style

author={Agostino Forestiero},
title={Self Recommendation in Peer to Peer Systems},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)},

in EndNote Style

JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)
TI - Self Recommendation in Peer to Peer Systems
SN - 978-989-758-052-9
AU - Forestiero A.
PY - 2014
SP - 332
EP - 336
DO - 10.5220/0005157603320336