@InCollection{     meredith2016-analysing,
    author       = {Meredith, David},
    year         = {2016},
    title        = {Analysing Music with Point-Set Compression Algorithms},
    abstract     = {This book provides an in-depth introduction and overview
                   of current research in computational music analysis. Its
                   seventeen chapters, written by leading researchers,
                   collectively represent the diversity as well as the
                   technical and philosophical sophistication of the work
                   being done today in this intensely interdisciplinary
                   field. A broad range of approaches are presented,
                   employing techniques originating in disciplines such as
                   linguistics, information theory, information retrieval,
                   pattern recognition, machine learning, topology, algebra
                   and signal processing. Many of the methods described draw
                   on well-established theories in music theory and analysis,
                   such as Forte's pitch-class set theory, Schenkerian
                   analysis, the methods of semiotic analysis developed by
                   Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative
                   Theory of Tonal Music. The book is divided into six parts,
                   covering methodological issues, harmonic and pitch-class
                   set analysis, form and voice-separation, grammars and
                   hierarchical reduction, motivic analysis and pattern
                   discovery and, finally, classification and the discovery
                   of distinctive patterns. As a detailed and up-to-date
                   picture of current research in computational music
                   analysis, the book provides an invaluable resource for
                   researchers, teachers and students in music theory and
                   analysis, computer science, music information retrieval
                   and related disciplines. It also provides a
                   state-of-the-art reference for practitioners in the music
                   technology industry.},
    address      = {Cham},
    booktitle    = {Computational Music Analysis},
    chapter      = {13},
    doi          = {10.1007/978-3-319-25931-4_13},
    editor       = {Meredith, David},
    isbn         = {9783319259314},
    issn         = {0098-7484},
    keywords     = {music analysis with computers},
    mendeley-tags= {music analysis with computers},
    pages        = {335--366},
    pmid         = {1689},
    publisher    = {Springer International Publishing},
    url          = {http://link.springer.com/10.1007/978-3-319-25931-4_13}
}

{"_id":"3WyYPSqLrSDsXzsre","bibbaseid":"meredith-analysingmusicwithpointsetcompressionalgorithms-2016","authorIDs":[],"author_short":["Meredith, D."],"bibdata":{"bibtype":"incollection","type":"incollection","author":[{"propositions":[],"lastnames":["Meredith"],"firstnames":["David"],"suffixes":[]}],"year":"2016","title":"Analysing Music with Point-Set Compression Algorithms","abstract":"This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.","address":"Cham","booktitle":"Computational Music Analysis","chapter":"13","doi":"10.1007/978-3-319-25931-4_13","editor":[{"propositions":[],"lastnames":["Meredith"],"firstnames":["David"],"suffixes":[]}],"isbn":"9783319259314","issn":"0098-7484","keywords":"music analysis with computers","mendeley-tags":"music analysis with computers","pages":"335–366","pmid":"1689","publisher":"Springer International Publishing","url":"http://link.springer.com/10.1007/978-3-319-25931-4_13","bibtex":"@InCollection{ meredith2016-analysing,\n author = {Meredith, David},\n year = {2016},\n title = {Analysing Music with Point-Set Compression Algorithms},\n abstract = {This book provides an in-depth introduction and overview\n of current research in computational music analysis. Its\n seventeen chapters, written by leading researchers,\n collectively represent the diversity as well as the\n technical and philosophical sophistication of the work\n being done today in this intensely interdisciplinary\n field. A broad range of approaches are presented,\n employing techniques originating in disciplines such as\n linguistics, information theory, information retrieval,\n pattern recognition, machine learning, topology, algebra\n and signal processing. Many of the methods described draw\n on well-established theories in music theory and analysis,\n such as Forte's pitch-class set theory, Schenkerian\n analysis, the methods of semiotic analysis developed by\n Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative\n Theory of Tonal Music. The book is divided into six parts,\n covering methodological issues, harmonic and pitch-class\n set analysis, form and voice-separation, grammars and\n hierarchical reduction, motivic analysis and pattern\n discovery and, finally, classification and the discovery\n of distinctive patterns. As a detailed and up-to-date\n picture of current research in computational music\n analysis, the book provides an invaluable resource for\n researchers, teachers and students in music theory and\n analysis, computer science, music information retrieval\n and related disciplines. It also provides a\n state-of-the-art reference for practitioners in the music\n technology industry.},\n address = {Cham},\n booktitle = {Computational Music Analysis},\n chapter = {13},\n doi = {10.1007/978-3-319-25931-4_13},\n editor = {Meredith, David},\n isbn = {9783319259314},\n issn = {0098-7484},\n keywords = {music analysis with computers},\n mendeley-tags= {music analysis with computers},\n pages = {335--366},\n pmid = {1689},\n publisher = {Springer International Publishing},\n url = {http://link.springer.com/10.1007/978-3-319-25931-4_13}\n}\n\n","author_short":["Meredith, D."],"editor_short":["Meredith, D."],"key":"meredith2016-analysing","id":"meredith2016-analysing","bibbaseid":"meredith-analysingmusicwithpointsetcompressionalgorithms-2016","role":"author","urls":{"Paper":"http://link.springer.com/10.1007/978-3-319-25931-4_13"},"keyword":["music analysis with computers"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"incollection","biburl":"https://hmb.sampaio.me/bibliografia.bib.txt","creationDate":"2019-04-22T13:04:36.111Z","downloads":0,"keywords":["music analysis with computers"],"search_terms":["analysing","music","point","set","compression","algorithms","meredith"],"title":"Analysing Music with Point-Set Compression Algorithms","year":2016,"dataSources":["n6MFY2CscQLDpJ7nT","RFLDZw5KyJdadDXDm"]}