ESWC'14 challenge on Concept-Level Sentiment Analysis (Contributo in atti di convegno)

Type
Label
  • ESWC'14 challenge on Concept-Level Sentiment Analysis (Contributo in atti di convegno) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1007/978-3-319-12024-9_1 (literal)
Alternative label
  • Reforgiato Recupero D.; Cambria E. (2014)
    ESWC'14 challenge on Concept-Level Sentiment Analysis
    in Communications in computer and information science (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Reforgiato Recupero D.; Cambria E. (literal)
Pagina inizio
  • 3 (literal)
Pagina fine
  • 20 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://www.scopus.com/inward/record.url?eid=2-s2.0-84908556143&partnerID=q2rCbXpz (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 475 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 475 (literal)
Rivista
Note
  • Scopu (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR, Via Gaifami 18, Catania, 95028, Italy; School of Computer Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore, Singapore (literal)
Titolo
  • ESWC'14 challenge on Concept-Level Sentiment Analysis (literal)
Abstract
  • With the introduction of social networks, blogs, wikis, etc., the users' behavior and their interaction in the Web have changed. As a consequence, people express their opinions and sentiments in a totally different way with respect to the past. All this information hinders potential business opportunities, especially within the advertising world, and key stakeholders need to catch up with the latest technology if they want to be at the forefront in the market. In practical terms, the automatic analysis of online opinions involves a deep understanding of natural language text, and it has been proved that the use of semantics improves the accuracy of existing sentiment analysis systems based on classical machine learning or statistical approaches. To this end, the Concept Level Sentiment Analysis challenge aims to provide a push in this direction offering the researchers an event where they can learn new approaches for the employment of Semantic Web features within their systems of sentiment analysis bringing to better performance and higher accuracy. The challenge aims to go beyond a mere word-level analysis of text and provides novel methods to process opinion data from unstructured textual information to structured machine-processable data. (literal)
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