@conference {13, title = {Weighted Markov Chain Model for Musical Composer Identification}, booktitle = {Applications of Evolutionary Computation}, year = {2011}, publisher = {Springer Berlin / Heidelberg}, organization = {Springer Berlin / Heidelberg}, abstract = {Several approaches based on the {\textquoteleft}Markov chain model{\textquoteright} have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorporating this information into a weighted variation of a first order Markov chain model. Additionally, we propose an evolutionary procedure that automatically tunes the introduced weights and exploits the full potential of the proposed model for tackling the composer identification task between two composers. Initial experimental results on string quartets of Haydn, Mozart and Beethoven suggest that the proposed model performs well and can provide insights on the inter onset and pitch intervals on the considered musical collection.}, doi = {10.1007/978-3-642-20520-0_34}, author = {M. A. Kaliakatsos-Papakostas and M. G. Epitropakis and M. N. Vrahatis}, editor = {Di Chio, Cecilia and Brabazon, Anthony and Di Caro, Gianni and Drechsler, Rolf and Farooq, Muddassar and Grahl, J{\"o}rn and Greenfield, Gary and Prins, Christian and Romero, Juan and Squillero, Giovanni and Tarantino, Ernesto and Tettamanzi, Andrea and Urquhart, Neil and Uyar, A.} }