One-touch access to music on mobile devices
Proceedings of the 6th international conference on Mobile and ubiquitous multimedia
A music information system automatically generated via Web content mining techniques
Information Processing and Management: an International Journal
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Exploring the music similarity space on the web
ACM Transactions on Information Systems (TOIS)
A model for serendipitous music retrieval
Proceedings of the 2nd Workshop on Context-awareness in Retrieval and Recommendation
Mining microblogs to infer music artist similarity and cultural listening patterns
Proceedings of the 21st international conference companion on World Wide Web
Personalization in multimodal music retrieval
AMR'11 Proceedings of the 9th international conference on Adaptive Multimedia Retrieval: large-scale multimedia retrieval and evaluation
A survey of music similarity and recommendation from music context data
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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We present a novel interface to (portable) music players that benefit from intelligently structured collections of audio files. For structuring, we calculate similarities between every pair of songs and model a travelling salesman problem (TSP) that is solved to obtain a playlist (i.e., the track ordering during playback) where the average distance between consecutive pieces of music is minimal according to the similarity measure. The similarities are determined using both audio signal analysis of the music tracks and Web-based artist profile comparison. Indeed, we show how to enhance the quality of the well-established methods based on audio signal processing with features derived from Web pages of music artists. Using TSP allows for creating circular playlists that can be easily browsed with a wheel as input device. We investigate the usefulness of four different TSP algorithms for this purpose. For evaluating the quality of the generated playlists, we apply a number of quality measures to two real-world music collections. It turns out that the proposed combination of audio and text-based similarity yields better results than the initial approach based on audio data only. We implemented an audio player as Java applet to demonstrate the benefits of our approach. Furthermore, we present the results of a small user study conducted to evaluate the quality of the generated playlists