Evaluation of similarity searching methods for music data in P2P networks
by Ioannis Karydis, Alexandros Nanopoulos, Apostolos N. Papadopoulos, Yannis Manolopoulos
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 1, No. 2, 2005

Abstract: In this paper, we focus on similarity searching for similar acoustic data over unstructured decentralised P2P networks. Similarity is measured in terms of time warping, which can cope with distortion that is naturally present when 'query by content' is performed. We propose a novel framework, which takes advantage of the absence of overhead in unstructured P2P networks and minimises the required traffic for all operations with the use of an intelligent sampling scheme. Within the proposed framework we adapt several existing algorithms for searching in P2P networks. Detailed experimental results show the efficiency of the proposed framework and the comparison between similarity searching algorithms.

Online publication date: Thu, 08-Dec-2005

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com