Pattern-Based Identification in P2P Systems

Abstract

This article presents a novel approach to search in shared audio file storages such as P2P based systems. The proposed method is based on the recognition of specific patterns in the audio contents in such a way extending the searching possibility from the description based model to the content based model. The importance of the real-time pattern recognition algorithms that are used on audio data for content-based searching in streaming media is rapidly growing (Liu, Wang, & Chen, 1998). The main problem of such algorithms is the optimal selection of the reference patterns (soundprints) used in the recognition procedure. The proposed method is based on distance maximization and is able to quickly choose the pattern that later will be used as reference by the pattern recognition algorithms (Richly, Kozma, Kovács, & Hosszú, 2001). The presented method called EMESE (experimental media-stream recognizer) is an important part of a lightweight content-searching method, which is suitable for the investigation of the networkwide shared file storages. The experimental measurement data shown in the article demonstrate the efficiency of the proposed procedure.