Alberto Pinto

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Content based music retrieval opens up large collections, both for the general public and music scholars. It basically enables the user to find (groups of) similar melodies, thus facilitating musicological research of many kinds. We present a graph spectral approach, new to the music retrieval field, in which melodies are represented as graphs, based on the(More)
The increasing diffusion of XML languages for the encoding of domain-specific multimedia information raises the need for new information retrieval models that can fully exploit structural information. An XML language specifically designed for music like MX allows queries to be made directly on the thematic material. The main advantage of such a system is(More)
The development of both musicologically based and efficient music information retrieval metrics to query large music database is crucial in modern music information retrieval, knowledge management and database research. Graph spectral representation of pitch class sequences has proved to outperform other pitch class based melodic similarity methods. Here(More)
The development of novel analytical tools to investigate the structure of music works is central in current music information retrieval research. In particular, music sum-marization aims at finding the most representative parts of a music piece (motifs) that can be exploited for an efficient music database indexing system. Here we present a novel approach(More)