Biblio
Filters: Author is Oramas, Sergio [Clear All Filters]
The AcousticBrainz Genre Dataset: Multi-Source, Multi-Level, Multi-Label, and Large-Scale.
20th International Society for Music Information Retrieval Conference (ISMIR 2019). Abstract
(2019).
MediaEval 2018 AcousticBrainz Genre Task: A baseline combining deep feature embeddings across datasets.
MediaEval 2018 Workshop.
(2018).
Natural Language Processing for Music Knowledge Discovery.
Journal of New Music Research. Abstract
(2018).
Multimodal Deep Learning for Music Genre Classification.
Transactions of the International Society for Music Information Retrieval. 1(1), 4-21. Abstract
(2018).
ELMDist: A vector space model with words and MusicBrainz entities.
Workshop on Semantic Deep Learning (SemDeep), collocated with ESWC 2017. Abstract
(2017).
A Deep Multimodal Approach for Cold-start Music Recommendation.
2nd Workshop on Deep Learning for Recommender Systems, at RecSys 2017. Abstract
(2017).
Freesound Datasets: A Platform for the Creation of Open Audio Datasets.
18th International Society for Music Information Retrieval Conference. Abstract
(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
(2017).
Knowledge Extraction and Representation Learning for Music Recommendation and Classification.
Department of Information and Communication Technologies. 203. Abstract
(2017).
Open Knowledge Extraction Challenge 2017.
Extended Semantic Web Conference (ESWC 2017).
(2017).
Open Knowledge Extraction Challenge 2017.
Extended Semantic Web Conference (ESWC 2017). Abstract
(2017).
ELMD: An Automatically Generated Entity Linking Gold Standard Dataset in the Music Domain.
Language Resources and Evaluation Conference (LREC 2016). 3312-3317. Abstract
(2016).
Finding and Expanding Hypernymic Relations in the Music Domain.
19th International Conference of the Catalan Association for Artificial Intelligence (CCIA). Abstract
(2016).
Information Extraction for Knowledge Base Construction in the Music Domain.
Data & Knowledge Engineering. 106, 70-83. Abstract
(2016).
Knowledge Is Out There: A New Step in the Evolution of Music Digital Libraries.
Fontes Artis Musicae. 63(4), 285-298. Abstract
(2016).
Sound and Music Recommendation with Knowledge Graphs.
ACM Transactions on Intelligent Systems and Technology (TIST). 8(2), 1-21. Abstract
(2016).
Exploring Customer Reviews for Music Genre Classification and Evolutionary Studies.
17th International Society for Music Information Retrieval Conference (ISMIR 2016). 150-156. Abstract
(2016).
A Semantic-based Approach for Artist Similarity.
16th International Society for Music Information Retrieval Conference. 100-106. Abstract
(2015).
Knowledge Acquisition from Music Digital Libraries.
International Association of Music Libraries and International Musicological Society IAML/IMS Conference. Abstract
(2015).
A Rule-Based Approach to Extracting Relations from Music Tidbits.
2nd Workshop on Knowledge Extraction from Text, WWW 2015. Abstract
(2015).
A Semantic Hybrid Approach for Sound Recommendation.
24th International World Wide Web Conference (WWW 2015). Abstract
(2015).
Extracting Relations from Unstructured Text Sources for Music Recommendation.
20th International Conference on Applications of Natural Language to Information Systems. Abstract
(2015).
FlaBase: Towards the Creation of a Flamenco Music Knowledge Base.
16th International Society for Music Information Retrieval Conference. Abstract
(2015).
Harvesting and Structuring Social Data in Music Information Retrieval.
Extended Semantic Web Conference (ESWC 2014). Abstract
(2014).
Extending Tagging Ontologies with Domain Specific Knowledge.
International Semantic Web Conference. 209-2012. Abstract
(2014).