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Computational Intelligence in Security for Information Systems Conference

CISIS 2015: International Joint Conference pp 189–200Cite as

CIOSOS: Combined Idiomatic-Ontology Based Sentiment Orientation System for Trust Reputation in E-commerce

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 369))

Abstract

Due to the abundant amount of Customer’s Reviews available in E-commerce platforms, Trust Reputation Systems remain reliable means to determine, circulate and restore the credibility and reputation of reviewers and their provided reviews. In fact before starting the process of Reputation score’s calculation, we need to develop an accurate Sentiment orientation System able to extract opinion expressions, analyze them and determine the sentiment orientation of the Review and then classify it into positive, negative and objective. In this paper, we propose a novel semi-supervised approach which is a Combined Idiomatic-Ontology based Sentiment Orientation System (CIOSOS) that realizes a domain-dependent sentiment analysis of reviews. The main contribution of the system is to expand the general opinion lexicon SentiWordNet to a custom-made opinion lexicon (SentiWordNet++) with domain-dependent “opinion indicators” as well as “idiomatic expressions”. The system relies also on a semi-supervised learning method that uses the general lexicon WordNet to identify synonyms or antonyms of the expanded terms and get their polarities from SentiWordNet and then store them in SentiWordNet++. The Sentiment polarity and the classification of the review provided by the CIOSOS is used as an input of our Reputation Algorithm proposed in previous papers in order to generate the Reputation score of the reviewer. We also provide an improvement in calculation method used to generate a “granular” reputation score of a feature or subfeature of the product.

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References

  1. Hamouda, A., Marei, M., Rohaim, M.: Building machine learning based senti-word lexicon for sentiment analysis. In: The Proceedings of the Journal of Advances in Information Technology, vol 2, issue 4, pp. 199–203. Nov 2011

    Google Scholar 

  2. Sharma, R., Nigam, S., Jain, R.: Mining of product reviews at aspect level. In: The Proceedings of the International Journal in Foundations of Computer Science & Technology (IJFCST), vol 4, issue 3, May 2014

    Google Scholar 

  3. Paramesha, K., Vishankar, V.: Optimization of cross domain sentiment analysis using SentiWordNet. In: The Proceedings of the International Journal in Foundations of Computer Science & Technology, vol 3, issue 5, p. 35. Sept 2013

    Google Scholar 

  4. khan, A., Baharudin, B.: Sentiment classification using sentence-level lexical based semantic orientation of online reviews. In: The Proceedings of the International journal of Computer Science Emerging Technology, vol. 2, issue 4, Aug 2011

    Google Scholar 

  5. Haider, S.Z.: An ontology based sentiment analysis a case study; Master Degree Project in Informatics

    Google Scholar 

  6. Kim, H-J., Song, M.: An ontology-based approach to sentiment classification of mixed opinions in online restaurant reviews. In: The Proceedings of the 5th International Conference, SocInfo 2013, pp. 95–108. Kyoto, Japan, November 25–27 2013

    Google Scholar 

  7. Hamdan, H., Béchet, F., Bellot, P.: Experiments with DBpedia, WordNet and SentiWordNet as resources for sentiment analysis in micro-blogging. In: The Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pp. 455–459. Atlanta, Georgia, USA

    Google Scholar 

  8. Khin Phyu Phyu Shein: Ontology based combined approach for sentiment classification. In: The Proceedings of the 3rd International Conference on Communications and Information Technology, pp. 112–115

    Google Scholar 

  9. Rahimi, H., El Bakkali, H.: A new trust reputation system for E-commerce applications references. In: The Proceedings of the International Journal of Computer Science Issues (IJCSI) (2014)

    Google Scholar 

  10. Sharma, R., Nigam, S., Jain, R.: Supervised opinion mining techniques: a survey. In: The Proceedings of the International Journal in Foundations of Computer Science & Technology (IJFCST), vol. 4, issue 3, May 2014

    Google Scholar 

  11. Dasgupta, S., Vincent, N.G.: Mine the easy, classify the hard: a semi-supervised approach to automatic sentiment classification. In: The Proceedings of the 47th Annual Meeting of the ACL and the 4th IJCNLP of the AFNLP, pp. 701–709. Suntec, Singapore, 2–7 August 2009

    Google Scholar 

  12. Anwer, N., Rashid, A., Hassan, V.: Feature based opinion mining of online free format customer reviews using frequency distribution and bayesian statistics. In: The Proceedings of the Networked Computing and Advanced Information Management (NCM), 2010 Sixth International Conference, pp. 57–62. 16–18 August 2010

    Google Scholar 

  13. Kaushik, C., Mishra, A.: A scalable, lexicon based technique for sentiment analysis. In: The Proceedings of the International Journal in Foundations of Computer Science & Technology (IJFCST), Vol. 4, No. 5, September 2014

    Google Scholar 

  14. Manning, C.D.: Part-of-speech tagging from 97 % to 100 %: is it time for some linguistics?. In: The Proceedings of the 12th International Conference on Computational linguistics and Intelligent Text Processing, pp. 171–189

    Google Scholar 

  15. Hu, M., Liu, B.: Mining and summarizing customer reviews. In: The Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168–177

    Google Scholar 

  16. Polpinij, J., Ghose, A.K.: An ontology-based sentiment classification methodology for online consumer reviews. In: the Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, vol. 01, pp. 518–524

    Google Scholar 

  17. Miller, G.A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K.: Introduction to WordNet: an on-line lexical database (Revised August 1993). In: The Proceedings of the International Journal of Lexicography, vol. 3, issue 4, pp. 235–244 (1990)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Information Security Research Team (ISeRT), University Mohamed V Souissi, ENSIAS, Rabat, Morocco

    Hasnae Rahimi & Hanan EL Bakkali

Authors
  1. Hasnae Rahimi
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  2. Hanan EL Bakkali
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Corresponding author

Correspondence to Hasnae Rahimi .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, Escuela Politécnica Superior, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. Department of Civil Engineering, Escuela Politécnica Superior, University of Burgos, Burgos, Spain

    Bruno Baruque

  3. Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  4. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  5. Plaza de la Merced S/N, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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© 2015 Springer International Publishing Switzerland

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Rahimi, H., Bakkali, H.E. (2015). CIOSOS: Combined Idiomatic-Ontology Based Sentiment Orientation System for Trust Reputation in E-commerce. In: Herrero, Á., Baruque, B., Sedano, J., Quintián, H., Corchado, E. (eds) International Joint Conference. CISIS 2015. Advances in Intelligent Systems and Computing, vol 369. Springer, Cham. https://doi.org/10.1007/978-3-319-19713-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-19713-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19712-8

  • Online ISBN: 978-3-319-19713-5

  • eBook Packages: EngineeringEngineering (R0)

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