Classification and data mining in musicology

Data in music are complex and highly structured. In this talk a number of descriptive and model-based methods are discussed that can be used as preprocessing devices before standard methods of classification, clustering etc. can be applied. The purpose of pre-processing is to incorporate prior knowledge in musicology and hence to filter out information that is relevant from the point of view of music theory. This is illustrated by a number of examples from classical music, including the analysis of scores and of musical performance.