Biblio

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O'Connell, J. (2011).  Musical Mosaicing with High Level Descriptors. Abstract
application/pdf iconOConnell-John-Master-thesis-2011.pdf
Oliveira, A. (2013).  A customizable, multi-parametric auditory display technique for theta-alpha neurofeedback training. Abstract
Ong, B. (2005).  Towards Automatic Music Structural Analysis Identifying Characteristic Within-Song Excerpts in Popular Music. Abstract
Ong, B., & Herrera P. (2005).  Semantic Segmentation Of Music Audio Contents. International Computer Music Conference. Abstract
Ong, B., Gómez E., & Streich S. (2006).  Automatic Extraction of Musical Structure Using Pitch Class Distribution Features. Abstract
Ong, B. (2007).  Structural Analysis and Segmentation of Music Signals. Department of Information and Communication Technologies. Abstract
Ong, B., & Herrera P. (2004).  Computing Structural Descriptions of Music through the Identification of Representative Excerpts from Audio Files. International Computer Music Conference (ICMC). Abstract
Oramas, S., Espinosa-Anke L., Sordo M., Saggion H., & Serra X. (2016).  ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain. Language Resources and Evaluation Conference (LREC 2016). 3312-3317. Abstract
Oramas, S., & Sordo M. (2015).  Knowledge Acquisition from Music Digital Libraries. International Association of Music Libraries and International Musicological Society IAML/IMS Conference. Abstract
application/pdf iconPresentation slides
Oramas, S., Sordo M., & Espinosa-Anke L. (2015).  A Rule-Based Approach to Extracting Relations from Music Tidbits. 2nd Workshop on Knowledge Extraction from Text, WWW 2015. Abstract
application/pdf iconsoramas_msordo_lespinsosa_ket2015.pdf
Oramas, S., Bogdanov D., & Porter A. (2018).  MediaEval 2018 AcousticBrainz Genre Task: A baseline combining deep feature embeddings across datasets. MediaEval 2018 Workshop.
Oramas, S., & Cornelis O. (2012).  Past, Present and Future in Ethnomusicology: The Computational challenge. ISMIR late breaking demo session, 13th International Society of Music Information Retrieval. Abstract
application/pdf iconLBD11.pdf
Oramas, S., & Sordo M. (2016).  Knowledge Is Out There: A New Step in the Evolution of Music Digital Libraries. Fontes Artis Musicae. 63(4), 285-298. Abstract
Oramas, S., Nieto O., Barbieri F., & Serra X. (2017).  Multi-label Music Genre Classification from Audio, Text and Images Using Deep Features. 18th International Society for Music Information Retrieval Conference (ISMIR 2017). Abstract
Oramas, S., Espinosa-Anke L., Lawlor A., Serra X., & Saggion H. (2016).  Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies. 17th International Society for Music Information Retrieval Conference (ISMIR 2016). 150-156. Abstract
Oramas, S., Gómez F., Gómez E., & Mora J. (2015).  FlaBase: Towards the Creation of a Flamenco Music Knowledge Base. 16th International Society for Music Information Retrieval Conference. Abstract
application/pdf iconflabase.pdf
Oramas, S., Espinosa-Anke L., Gómez F., & Serra X. (2018).  Natural Language Processing for Music Knowledge Discovery. Journal of New Music Research. Abstract
Oramas, S., Nieto O., Sordo M., & Serra X. (2017).  A Deep Multimodal Approach for Cold-start Music Recommendation. 2nd Workshop on Deep Learning for Recommender Systems, at RecSys 2017. Abstract
Oramas, S., Espinosa-Anke L., Sordo M., Saggion H., & Serra X. (2016).  Information Extraction for Knowledge Base Construction in the Music Domain. Data & Knowledge Engineering. 106, 70-83. Abstract
Oramas, S., Sordo M., Espinosa-Anke L., & Serra X. (2015).  A Semantic-based Approach for Artist Similarity. 16th International Society for Music Information Retrieval Conference. 100-106. Abstract
application/pdf iconpostprint version
Oramas, S., Sordo M., & Serra X. (2014).  Automatic Creation of Knowledge Graphs from Digital Musical Document Libraries. Conference in Interdisciplinary Musicology. Abstract
application/pdf iconCIM14_MAIN.pdf
Oramas, S., Barbieri F., Nieto O., & Serra X. (2018).  Multimodal Deep Learning for Music Genre Classification. Transactions of the International Society for Music Information Retrieval. 1(1), 4-21. Abstract
Oramas, S. (2014).  Harvesting and Structuring Social Data in Music Information Retrieval. Extended Semantic Web Conference (ESWC 2014). Abstract
application/pdf iconPhD_Prop_SergioOramas.pdf
Oramas, S. (2017).  Knowledge Extraction and Representation Learning for Music Recommendation and Classification. Department of Information and Communication Technologies. 203. Abstract
Oramas, S., Ostuni V. C., Di Noia T., Serra X., & Di Sciascio E. (2016).  Sound and Music Recommendation with Knowledge Graphs. ACM Transactions on Intelligent Systems and Technology (TIST). 8(2), 1-21. Abstract
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