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Extracting Relations from Unstructured Text Sources for Music Recommendation [chapter]

Mohamed Sordo, Sergio Oramas, Luis Espinosa-Anke
2015 Lecture Notes in Computer Science  
This paper presents a method for the generation of structured data sources for music recommendation using information extracted from unstructured text sources.  ...  The extracted entities and relations are represented as a graph, from which the recommendations are computed.  ...  Acknowledgments The authors would like to thank Miguel Ballesteros for his valuable advice and the subjects of the online experiment for their feedback.  ... 
doi:10.1007/978-3-319-19581-0_33 fatcat:wgygeuaa7jhbdp7rnj2qtl42fi

Harvesting and Structuring Social Data in Music Information Retrieval [chapter]

Sergio Oramas
2014 Lecture Notes in Computer Science  
We propose a methodology that combines Social Media Mining, Knowledge Extraction and Natural Language Processing techniques, to extract meaningful context information from social data.  ...  By using the extracted information we aim to improve retrieval, discovery and annotation of music and sound resources. We define three different scenarios to test and develop our methodology.  ...  We will focus our research in the extraction of knowledge from music-related context information sources in the Web.  ... 
doi:10.1007/978-3-319-07443-6_55 fatcat:nbksmdhwj5a2vcyzy76e5tpzie

Flabase: Towards The Creation Of A Flamenco Music Knowledge Base

Sergio Oramas, Francisco Gómez 0001, Emilia Gómez, Joaquín Mora
2015 Zenodo  
We thank Rafael Infante and José Ruiz Fuentes for the provided content.  ...  Next, new knowledge is extracted from unstructured harvested texts and employed to populate the knowledge base. For this purpose, an entity linking system has been expressly developed.  ...  We re-utilized most of the classes and some properties from the Music Ontology 9 , a standard model for publishing music-related data.  ... 
doi:10.5281/zenodo.1417183 fatcat:xnkiwdrp4vbk5ac4ceoljmkl2u

Knowledge Extraction And Representation Learning For Music Recommendation And Classification

Sergio Oramas, Xavier Serra
2017 Zenodo  
To this end, we first focus on the problem of linking music-related texts with online knowledge repositories and on the automated construction of music knowledge bases.  ...  Next, we focus on learning new data representations from multimodal content using deep learning architectures, addressing the problems of cold-start music recommendation and multi-label music genre classification  ...  On the one hand, we work on new methodologies for the extraction of high-level semantic representations from music-related unstructured texts.  ... 
doi:10.5281/zenodo.1048497 fatcat:kdh5jhvocbh3riwln6n2f756su

Knowledge Extraction And Representation Learning For Music Recommendation And Classification

Sergio Oramas, Xavier Serra
2017 Zenodo  
To this end, we first focus on the problem of linking music-related texts with online knowledge repositories and on the automated construction of music knowledge bases.  ...  Next, we focus on learning new data representations from multimodal content using deep learning architectures, addressing the problems of cold-start music recommendation and multi-label music genre classification  ...  On the one hand, we work on new methodologies for the extraction of high-level semantic representations from music-related unstructured texts.  ... 
doi:10.5281/zenodo.1100973 fatcat:yfpmc6qxbbakjp6qzvywyoaoci

Culture-Aware Approaches to Modeling and Description of Intonation Using Multimodal Data [chapter]

Gopala Krishna Koduri
2015 Lecture Notes in Computer Science  
As part of this, we propose novel approaches to describe intonation in audio music recordings and to use and adapt the semantic web infrastructure to complement this with the knowledge extracted from text  ...  In a step towards addressing this, the thesis draws upon multimodal data sources concerning art music traditions, extracting culturally relevant and musically meaningful information about melodic intervals  ...  The former draws upon data sources such as tags, lyrics and unstructured text for applications ranging from playlist generation and auto tagging, to music recommendation, search engines and interfaces  ... 
doi:10.1007/978-3-319-17966-7_30 fatcat:jk5w2tfnsbbizmshuyuo5r5yge

Constructing a Knowledge Base for Entertainment by Interlinking Multiple Data Sources

Haklae Kim
2017 EAI Endorsed Transactions on Industrial Networks and Intelligent Systems  
extraction of large-scale data, and knowledge transformation from them.  ...  This paper describes a knowledge base for entertainment domains, including movies, music, and celebrities.  ...  Knowledge extraction from text employs the distant supervision method [13] to extract relations between recognized entities, which handle a task in two stages.  ... 
doi:10.4108/eai.1-2-2017.152152 fatcat:z43xgxo2pba6nhsnppjqz6kgwq

PKG

Yu Yang, Jiangxu Lin, Xiaolian Zhang, Meng Wang
2022 Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval  
In this paper, we demonstrate a novel system for integrating the data of a user from different sources into a Personal Knowledge Graph, i.e., PKG.  ...  The constructed PKG allows the system makes reasonable and accurate recommendations for users by a "neural + symbolic" approach across different services.  ...  Social APP has the lowest recommendation accuracy because unstructured texts have higher requirements for the terms given.  ... 
doi:10.1145/3477495.3531671 fatcat:ogztzdkdtzecxk7dx5yfsu4qmq

Computing Semantic Relatedness using DBPedia

José Paulo Leal, Vânia Rodrigues, Ricardo Queirós, Marc Herbstritt
2012 Symposium on Languages, Applications and Technologies  
To validate the proposed approach Shakti was used to recommend web pages on a Portuguese social site related to alternative music and the results of that experiment are reported in this paper.  ...  This algorithm was implemented on a tool called Shakti that extract relevant ontological data for a given domain from DBpedia using its SPARQL endpoint.  ...  The authors wish also to thank the reviewers for their helpful comments.  ... 
doi:10.4230/oasics.slate.2012.133 dblp:conf/slate/LealRQ12 fatcat:w3w76qqrqzdktcoutspgi2d4oy

A Rule-Based Approach to Extracting Relations from Music Tidbits

Sergio Oramas, Mohamed Sordo, Luis Espinosa-Anke
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
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 music genres.  ...  The authors would like to thank Miguel Ballesteros for his valuable advice.  ... 
doi:10.1145/2740908.2741709 dblp:conf/www/OramasSA15 fatcat:3vnwk64trralppvmvf6hibxnwq

Trends in content-based recommendation

Pasquale Lops, Dietmar Jannach, Cataldo Musto, Toine Bogers, Marijn Koolen
2019 User modeling and user-adapted interaction  
Early work by Passant (2010) , for example, used DBpedia as an external knowledge source for music recommendation.  ...  From an algorithmic perspective, these papers often rely on deep learning approaches for feature extraction or recommendation.  ... 
doi:10.1007/s11257-019-09231-w fatcat:ftunw4mq5vgojifno3yqklfwbq

Transfer Meets Hybrid: A Synthetic Approach for Cross-Domain Collaborative Filtering with Text [article]

Guangneng Hu, Yu Zhang, Qiang Yang
2019 arXiv   pre-print
TMH attentively extracts useful content from unstructured text via a memory module and selectively transfers knowledge from a source domain via a transfer network.  ...  We propose a novel neural model to smoothly enable Transfer Meeting Hybrid (TMH) methods for cross-domain recommendation with unstructured text in an end-to-end manner.  ...  Convolutional networks (CNNs) have been used to extract the features from audio signals for music recommendation [49] and from image for product [16] and multimedia [6] recommendation.  ... 
arXiv:1901.07199v1 fatcat:ti7l7rv2vzca7cauwh4iidaceq

Innovation and Integration Development of the Cultural Industry Based on Mapping Knowledge Domains

Jiangong Lian, Dan Liang, Le Sun
2022 Computational Intelligence and Neuroscience  
Event extraction can collect relevant information from unstructured text data to achieve a complete description of entities.  ...  Unstructured extraction is to extract knowledge from free text, including the following three modules: entity, relationship, and event. e extraction process is mainly based on the existing annotation rules  ... 
doi:10.1155/2022/4725196 pmid:35855790 pmcid:PMC9288315 fatcat:wl3htstfufasncx2wxk7fnk3f4

Using proximity to compute semantic relatedness in RDF graphs

José Leal
2013 Computer Science and Information Systems  
This algorithm was implemented on a tool called Shakti that extracts relevant ontological data for a given domain from DBpedia -a community effort to extract structured data from the Wikipedia.  ...  To validate the proposed approach Shakti was used to recommend web pages on a Portuguese social site related to alternative music and the results of that experiment are also reported.  ...  The author wishes to thank to Vânia Rodrigues for her collaboration on the implementation o Shakti, and to Ricardo Queirós, João Delgado and the anonymous reviewers for their helpful comments.  ... 
doi:10.2298/csis121130060l fatcat:qf5cfgmvizd75kx5756ucxg6su

Knowledge Extraction Framework for Building a Largescale Knowledge Base

Haklae Kim, Liang He, Ying Di
2016 EAI Endorsed Transactions on Industrial Networks and Intelligent Systems  
Thus, this framework can be used for extracting a set of knowledge entities from large-scale web documents.  ...  Simultaneously, various intelligent services are available for us such as virtual assistants, semantic search and intelligent recommendation.  ...  For processing various unstructured data sources, specific extraction engines are developed for various formats, such as metadata and web tables from HTML web pages and unstructured and plain text.  ... 
doi:10.4108/eai.21-4-2016.151157 fatcat:gujdvqtylvezpleomktrooc274
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