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This paper, introduces the application of Content-Based Music Information Retrieval (CBMIR) in wireless ad-hoc networks. We investigate for the first time the challenges posed by the wireless medium and recognise the factors that require optimisation. We propose novel techniques, which attain a significant reduction in both response times and traffic,(More)
Measuring similarity of two musical pieces is an ill-defined problem for which recent research on contextual information, assigned as free-form text (tags) in social networking services, has shown to be highly effective. Nevertheless, approaches based on contextual information require adequate amount of tags per musical datum in order to be effective. In(More)
This paper presents an algorithm that efficiently retrieves audio data similar to an audio query. The proposed method utilises a feature extraction method for acoustical music sequences. The extracted features are grouped by Minimum Bounding Rectangles (MBRs) and indexed by means of a spatial access method. We also present a novel false alarm resolution(More)
In this work, we study collective intelligence behavior of Web users that share and watch video content. We propose that the aggre-gated users' video activity exhibits characteristic patterns that may be used in order to infer important video scenes thus leading to collective intelligence concerning the video content. In particular, we have utilised a(More)
This paper presents a genre classification algorithm for music data. The proposed methodology relies on note pitch and duration features, derived from the repeating terns and duration histograms of a musical piece, respectively. Note-information histograms have a great capability in capturing a fair amount of information regarding harmonic as well as(More)
This paper presents a case-study of the effectiveness of a trained system into classifying Greek songs according to their audio characteristics or/and their lyrics into moods. We examine how the usage of different algorithms, featureset combinations and pre-processing parameters affect the precision and recall percentages of the classification process for(More)
Internet-based interactive TV is an emerging field affected by advances in various research areas including communication, interactivity, network efficiency, content management and aesthetics. Despite constantly reducing costs in the area of broadcast infrastructure development, this new medium has yet to claim its market position and recognition. The large(More)
This work studies collective intelligence behavior of Web users that share and watch video content. Accordingly, it is proposed that the aggregated users' video activity exhibits characteristic patterns. Such patterns may be used in order to infer important video scenes leading thus to collective intelligence concerning the video content. To this end,(More)
This paper introduces the problem of discovering maximum-length repeating patterns in music objects. A novel algorithm is presented for the extraction of this kind of patterns from a melody music object. The proposed algorithm discovers all maximum-length repeating patterns using an " aggressive " accession during searching, by avoiding costly repetition(More)