Manuela Angioni, Franco Tuveri


Understanding the meaning of a text depends on the knowledge the reader has about the topic addressed in a document, starting from the most complex concept to the simplest one. The representation of the knowledge is generally performed by ontologies, semantic networks, or typified by statistical algorithms able to organize the contents according to rules based on frequency of terms or synsets. The Opinion Mining is a way to go beyond text categorization through the analysis of the opinions related to a specific topic: a product, a service, a tourist location, etc. In this paper we propose to apply our experience in the semantic analysis of textual resources to the Opinion Mining task, with the aim to propose a different approach to the extraction of feature terms, performing a contextualisation by means of semantic categorisation, a semantic net of concept and by a set of qualities associated to the sense expressed by adjectives and adverbs.


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Paper Citation

in Harvard Style

Angioni M. and Tuveri F. (2011). A SEMANTIC APPROACH TO THE EXTRACTION OF FEATURE TERMS . In Proceedings of the 6th International Conference on Software and Database Technologies - Volume 2: ICSOFT, ISBN 978-989-8425-77-5, pages 402-407. DOI: 10.5220/0003602204020407

in Bibtex Style

author={Manuela Angioni and Franco Tuveri},
booktitle={Proceedings of the 6th International Conference on Software and Database Technologies - Volume 2: ICSOFT,},

in EndNote Style

JO - Proceedings of the 6th International Conference on Software and Database Technologies - Volume 2: ICSOFT,
SN - 978-989-8425-77-5
AU - Angioni M.
AU - Tuveri F.
PY - 2011
SP - 402
EP - 407
DO - 10.5220/0003602204020407