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2015
Springer

Extracting Relations from Unstructured Text Sources for Music Recommendation

4 years 2 months ago
Extracting Relations from Unstructured Text Sources for Music Recommendation
Abstract. This paper presents a method for the generation of structured data sources for music recommendation using information extracted from unstructured text sources. The proposed method identifies entities in text that are relevant to the music domain, and then extracts semantically meaningful relations between them. The extracted entities and relations are represented as a graph, from which the recommendations are computed. A major advantage of this approach is that the recommendations can be conveyed to the user using natural language, thus providing an enhanced user experience. We test our method on texts from songfacts.com, a website that provides facts and stories about songs. The extracted relations are evaluated intrinsically by assessing their linguistic quality, as well as extrinsically by assessing the extent to which they map an existing music knowledge base. Finally, an experiment with real users is performed to assess the suitability of the extracted knowledge for mus...
Mohamed Sordo, Sergio Oramas, Luis Espinosa Anke
Added 15 Apr 2016
Updated 15 Apr 2016
Type Journal
Year 2015
Where NLDB
Authors Mohamed Sordo, Sergio Oramas, Luis Espinosa Anke
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