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Browsing Congressos (Departament de Tecnologies de la Informació i les Comunicacions) by Author "Oramas, Sergio"

Browsing Congressos (Departament de Tecnologies de la Informació i les Comunicacions) by Author "Oramas, Sergio"

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  • Oramas, Sergio; Nieto Caballero, Oriol; Sordo, Mohamed; Serra, Xavier (ACM Association for Computer Machinery, 2017)
    An increasing amount of digital music is being published daily. Music streaming services often ingest all available music, but this poses a challenge: how to recommend new artists for which prior knowledge is scarce? In ...
  • Oramas, Sergio; Sordo, Mohamed; Espinosa-Anke, Luis (ACM Association for Computer Machinery, 2015)
    This paper presents a rule based approach to extracting relations from unstructured music text sources. The proposed approach identifies and disambiguates musical entities in text, such as songs, bands, persons, albums and ...
  • Ostuni, Vito Claudio; Di Noia, Tommaso; Di Sciascio, Eugenio; Oramas, Sergio; Serra, Xavier (ACM Association for Computer Machinery, 2015)
    In this work we describe a hybrid recommendation approach for recommending sounds to users by exploiting and semantically enriching textual information such as tags and sounds descriptions. As a case study we used Freesound, ...
  • Oramas, Sergio; Sordo, Mohamed; Espinosa-Anke, Luis; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2015)
    This paper describes and evaluates a method for computing artist similarity from a set of artist biographies. The/nproposed method aims at leveraging semantic information present in these biographies, and can be divided ...
  • Oramas, Sergio; Sordo, Mohamed; Serra, Xavier (Society for Interdisciplinary Musicology, 2014)
    Most of the current musicological knowledge is present in printed books and manuscripts. In the last years greats efforts have been done in order to digitize and make available these documents in form of Digital Libraries. ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Sordo, Mohamed; Saggion, Horacio; Serra, Xavier (European Language Resources Association, 2016)
    In this paper we present a gold standard dataset for Entity Linking (EL) in the Music Domain. It contains thousands of musical named entities such as Artist, Song or Record Label, which have been automatically annotated ...
  • Espinosa-Anke, Luis; Oramas, Sergio; Saggion, Horacio; Serra, Xavier (Springer, 2017)
    Music consumption habits as well as the Music market have changed dramatically due to the increasing popularity of digital audio and streaming services. Today, users are closer than ever to a vast number of songs, albums, ...
  • Oramas, Sergio; Espinosa-Anke, Luis; Lawlor, Aonghus; Serra, Xavier; Saggion, Horacio (International Society for Music Information Retrieval (ISMIR), 2016)
    In this paper, we explore a large multimodal dataset of about 65k albums constructed from a combination of Amazon customer reviews, MusicBrainz metadata and AcousticBrainz audio descriptors. Review texts are further enriched ...
  • Font Corbera, Frederic; Oramas, Sergio; Fazekas, György; Serra, Xavier (CEUR Workshop Proceedings, 2014)
    Currently proposed tagging ontologies are mostly focused on the definition of a common schema for representing the agents involved in a tagging process. In this paper we describe preliminary research around the idea of ...
  • Sordo, Mohamed; Oramas, Sergio; Espinosa-Anke, Luis (Springer, 2015)
    This paper presents a method for the generation of struc- tured data sources for music recommendation using information extracted from unstructured text sources. The proposed method identi es entities in text that are ...
  • Espinosa-Anke, Luis; Oramas, Sergio; Camacho-Collados, Jose; Saggion, Horacio (2016)
    Lexical taxonomies are tree or directed acyclic graph-like structures where each node represents a concept and each edge encodes a binary hypernymic (is-a) relation. These lexical resources are useful for AI tasks like ...
  • Oramas, Sergio; Gómez, Francisco; Gómez Gutiérrez, Emilia, 1975-; Mora, Joaquín (International Society for Music Information Retrieval (ISMIR), 2015)
    Online information about flamenco music is scattered over different sites and knowledge bases. Unfortunately, there is no common repository that indexes all these data. In this work, information related to flamenco ...
  • Fonseca, Eduardo; Pons Puig, Jordi; Favory, Xavier; Font Corbera, Frederic; Bogdanov, Dmitry; Ferraro, Andrés; Oramas, Sergio; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Openly available datasets are a key factor in the advancement of data-driven research approaches, including many of the ones used in sound and music computing. In the last few years, quite a number of new audio datasets ...
  • Ferraro, Andrés; Oramas, Sergio; Quadrana, Massimo; Serra, Xavier (CEUR Workshop Proceedings, 2020)
    Music recommendation engines play a pivotal role in connecting artists with their listeners. Optimizing myopically only for user satisfaction may lead systems to recommend just a small fraction of all the available artists, ...
  • Oramas, Sergio; Bogdanov, Dmitry; Porter, Alastair (CEUR Workshop Proceedings, 2018)
    In this paper we present a baseline approach for the MediaEval 2018 AcousticBrainz Genre Task that takes advantage of stacking multiple feature embeddings learned on individual genre datasets by simple deep learning ...
  • Oramas, Sergio; Ferraro, Andrés; Correya, Albin Andrew; Serra, Xavier (2017)
    In this work, we present MEL, the first Music Entity Linking system. MEL is able to identify mentions of musical entities (e.g., album, songs, and artists) in free text, and disambiguate them to a music knowledge base, ...
  • Korzeniowski, Filip; Nieto Caballero, Oriol; McCallum, Matthew C.; Won, Minz; Oramas, Sergio; Schmidt, Erik M. (International Society for Music Information Retrieval (ISMIR), 2020)
    The mood of a song is a highly relevant feature for exploration and recommendation in large collections of music. These collections tend to require automatic methods for predicting such moods. In this work, we show that ...
  • Oramas, Sergio; Nieto Caballero, Oriol; Barbieri, Francesco; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Music genres allow to categorize musical items that share common characteristics. Although these categories are not mutually exclusive, most related research is traditionally focused on classifying tracks into a single ...
  • Won, Minz; Oramas, Sergio; Nieto Caballero, Oriol; Gouyon, Fabien; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    Tag-based music retrieval is crucial to browse large-scale mu-sic libraries efficiently. Hence, automatic music tagging has been actively explored, mostly as a classification task, which has an inherent limitation: a fixed ...
  • Speck, René; Röder, Michael; Oramas, Sergio; Espinosa-Anke, Luis; Ngonga Ngomo, Axel-Cyrille (Springer, 2017)
    The Open Knowledge Extraction Challenge invites researchers and practitioners from academia as well as industry to compete to the aim of pushing further the state of the art of knowledge extraction from text for the Semantic ...

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