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Collaborative filtering recommender systems often use nearest neighbor methods to identify candidate items. In this paper we present an inverted neighborhood model, k-Furthest Neighbors, to identify less ordinary neighborhoods for the purpose of creating more diverse recommendations. The approach is evaluated two-fold, once in a traditional information(More)
Modern collections of symbolic and audio music content provide unprecedented possibilities for musicological research , but traditional qualitative evaluation methods cannot realistically cope with such amounts of data. We are interested in harmonic analysis and propose key-independent chord idioms derived from a bottom-up analysis of musical data as a new(More)
A sample of the Myspace artist network is examined to investigate the relationship between social connectivity and audio-based similarity. Audio data from the Myspace artist pages is analyzed using well-established signal-based music information retrieval techniques. In addition to showing that the Myspace artist network exhibits many of the properties(More)
Community detection methods from complex network theory are applied to a subset of the Myspace artist network to identify groups of similar artists. Methods based on the greedy optimization of modularity and random walks are used. In a second iteration, inter-artist audio-based similarity scores are used as input to enhance these community detection(More)
We have sampled the artist social network of Myspace and to it applied the pairwise relational connectivity measure Minimum cut/Maximum flow. These values are then compared to a pairwise acoustic Earth Mover's Distance measure and the relationship is discussed. Further, a means of constructing playlists using the maximum flow value to exploit both the(More)
Many solutions for the reuse and remixing of MIR methods and the tools implementing them have been introduced over recent years. Proposals for achieving the necessary interoperability have ranged from shared software libraries and interfaces, through common frameworks and portals, to standardised file formats and metadata. Each proposal shares the desire to(More)
—This paper presents an extensive analysis of a sample of a social network of musicians. The network sample is first analyzed using standard complex network techniques to verify that it has similar properties to other web-derived complex networks. Content-based pairwise dissimilarity values between the musical data associated with the network sample are(More)
Playlists are a natural delivery method for music recommendation and discovery systems. Recommender systems offering playlists must strive to make them relevant and enjoyable. In this paper we survey many current means of generating and evaluating playlists. We present a means of comparing playlists in a reduced dimensional space through the use of(More)
Existing semantic representations of music analysis encapsulate narrow sub-domain concepts and are frequently scoped by the context of a particular MIR task. Segmentation is a crucial abstraction in the investigation of phenomena which unfold over time; we present a Segment Ontology as the backbone of an approach that models properties from the(More)