A SEMANTIC APPROACH TO THE EXTRACTION OF FEATURE TERMS

Manuela Angioni, Franco Tuveri

Abstract

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.

References

  1. Akkaya, C., Wiebe, J., Mihalcea, R., 2009. Subjectivity word sense disambiguation. In: Conference on Empirical Methods in Natural Language Processing, Singapore, The Association for Computational Linguistics.
  2. Angioni, M., Demontis, R., Tuveri, F., 2008a. A SemanticApproach for Resource Cataloguing and Query Resolution. Communications of SIWN. Special Issue on Distributed Agent-based Retrieval Tools.
  3. Angioni, M., Demontis, R., Deriu, M., Tuveri, F., 2008b. SemanticNet: a WordNet-based Tool for the Navigation of Semantic Information. In: Proceedings of GWC 2008b. University of Szeged.
  4. Atserias, J., Casas, B., Comelles, E., González, M., Padró, L., Padró, M., 2006. FreeLing 1.3: Syntactic and semantic services in an open-source NLP library. In Proceedings of the fifth international conference on Language Resources and Evaluation (LREC 2006), ELRA. Genoa, Italy. http://nlp.lsi.upc.edu/freeling
  5. Benamara, F., Cesarano, C., Picariello, A., Reforgiato, D., Subrahmanian, V.S., 2007. Sentiment Analysis: Adjectives and Adverbs are better than Adjectives Alone. In Proceedings of ICWSM 07 International Conference on Weblogs and Social Media, pp. 203- 206.
  6. Crimson Hexagon, 2009. Listen, Understand, Act. How a listening platform provides actionable insight. http://www.crimsonhexagon.com/PDFs/Crimson_Hex agon_Listen_Understand_Feb_2009.pdf
  7. Ding, X., Liu, B., Yu, P.S., 2008. A Holistic LexiconBased Approach to Opinion Mining. WSDM 7808 Proceedings of the international conference on Web search and web data mining, ACM New York, NY, USA.
  8. Esuli, A. Sebastiani, F., 2007. PageRanking WordNet synsets: An application to Opinion Mining Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics Volume: 45, Issue: June, Publisher: Association for Computational Linguistics, Pages: 424-431
  9. Hatzivassiloglou, V., McKeown, K., 1997. Predicting the Semantic Orientation of Adjectives. In: Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, p.174-181, Madrid, Spain
  10. Lee, D., Jeong, O.R., Lee, S., 2008. Opinion Mining of customer feedback data on the web. In: ICUIMC 7808 Proceedings of the 2nd international conference on Ubiquitous information management and communication
  11. Magnini, B., Strapparava, C., Pezzulo, G., Gliozzo, A., 2002. The Role of Domain Information in Word Sense Disambiguation. Natural Language Engineering, special issue on Word Sense Disambiguation, 8(4), pp. 359-373, Cambridge University Press
  12. Magnini, B., Strapparava, C., 2004. User Modelling for News Web Sites with Word Sense Based Techniques. User Modeling and User-Adapted Interaction 14(2), pp. 239-257
  13. Miller, G., 1998. WordNet: An Electronic Lexical Database, Bradford Books
  14. Pang, B., Lee, L., Vaithyanathan, S., 2002. Thumbs up? Sentiment Classification using Machine Learning Techniques CoRR cs.CL/0205070
  15. Popescu, A.M., Etzioni, O, 2005. Extracting Product Features and Opinions from Reviews. Proceedings of the 2005 Conference on Empirical Methods in Natural Language Processing.(EMNLP'05).
  16. Rentoumi, V., Giannakopoulos, G., 2009. Sentiment analysis of figurative language using a word sense disambiguation approach. In: International Conference on Recent Advances in Natural Language Processing (RANLP 2009), Borovets, Bulgaria, The Association for Computational Linguistics
  17. Scaffidi, C., Bierhoff, K., Chang, E., Felker, M., Ng, Chun Jin, H., 2007. Red Opal: product-feature scoring from reviews. ACM Conference on Electronic Commerce 2007: 182-191
  18. Sebastiani, F., 2002. Machine learning in automated text categorization. ACM Computing Surveys, 34(1):1-47.
  19. Turney, P.D., 2002. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: ACL (40th Annual Meeting of the Association for Computational Linguistics). Philadelphia, Pennsylvania, USA: ACL.
  20. Vossen, P.(ed), 1998. EuroWordNet: A Multilingual Database with Lexical Semantic Networks, Kluwer Academic Publishers, Dordrecht.
  21. Yi, J., Nasukawa, T., Bunescu, R., Niblack, W., 2003. Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques. In: Proceedings of the IEEE International Conference on Data Mining.
  22. Yi, J., Niblack, W., 2005. Sentiment Mining in WebFountain. In: Proceeding ICDE 7805, 21st International Conference on Data Engineering IEEE Computer Society. Washington, DC, USA
  23. Zhai, Z., Liu, B., Xu, H., Jia, P., 2010. Grouping Product Features Using Semi-Supervised Learning with SoftConstraints. In: Proceedings of the 23rd International Conference on Computational Linguistics (COLING2010), Beijing, China.
Download


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

@conference{icsoft11,
author={Manuela Angioni and Franco Tuveri},
title={A SEMANTIC APPROACH TO THE EXTRACTION OF FEATURE TERMS},
booktitle={Proceedings of the 6th International Conference on Software and Database Technologies - Volume 2: ICSOFT,},
year={2011},
pages={402-407},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003602204020407},
isbn={978-989-8425-77-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Software and Database Technologies - Volume 2: ICSOFT,
TI - A SEMANTIC APPROACH TO THE EXTRACTION OF FEATURE TERMS
SN - 978-989-8425-77-5
AU - Angioni M.
AU - Tuveri F.
PY - 2011
SP - 402
EP - 407
DO - 10.5220/0003602204020407