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Polibits

versión On-line ISSN 1870-9044

Polibits  no.41 México ene./jun. 2010

 

Special section: processing of semantic information

 

Análisis de Opiniones con Ontologías

 

Opinion Mining using Ontolgies

 

Enrique Vallés Balaguer1, Paolo Rosso1, Angela Locoro2 y Viviana Mascardi2

 

1 NLE Lab – ELiRF, DSIC, Universidad Politecnica de Valencia, Valencia, España (e–mail: evalles@dsic.upv.es, prosso@dsic.upv.es).

2 DISI, Università degli Studi di Genova, Genova, Italia (e–mail: angela.locoro@unige.it, viviana.mascardi@unige.it).

 

Manuscrito recibido el 24 de febrero del 2010.
Manuscrito aceptado para su publicación el 31 de mayo del 2010.

 

Resumen

En este artículo presentamos un trabajo sobre análisis de opiniones llevado a cabo gracias a un enfoque innovador basado en fusión de ontologías. El objetivo de este trabajo es permitir que dos empresas puedan intercambiar y compartir los resultados de los análisis de las opiniones de sus productos y servicios.

Palabras clave: Minería de opiniones, mapeo y fusión de ontologías, Web 2.0, Empresa 2.0.

 

Abstract

In this paper we present a work dealing with opinion analysis carried out thanks to an innovative approach based on ontology matching. The aim of this work is to allow two enterprises to share and merge the results of opinion analyses on their own products and services.

Key words: Opinion mining, ontology matching and merging, Web 2.0, Enterprise 2.0.

 

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AGRADECIMIENTOS

El trabajo de los dos primeros autores se engloba dentro del proyecto del MICINN: TEXT–ENTERPRISE 2.0: Técnicas de Comprensión de textos aplicadas á las necesidades de la Empresa 2.0 (TIN2009–13391–C04–03). El trabajo ha sido el resultado de una estancia de Erasmus–Master de 4 meses en la Universidad de Genova.

 

REFERENCIAS

[1] J. Zabin and A. Jefferies, "Social media monitoring and analysis: Generating consumer insights from online conversation," Aberdeen Group Benchmark Report, January 2008.         [ Links ]

[2] T. Wilson, J. Wiebe, and R. Hwa, "Just how mad are you? finding strong and weak opinion clauses," AAAAI'04: Proceedings of the 19th national conference on Artifical intelligence, pp. 761–769, 2004.         [ Links ]

[3] L. Zhou and P. Chaovalit, "Ontology–supported polarity mining," Journal of the American Society for Information Science and Technology, vol. 59, no. 1, pp. 98–110, 2008.         [ Links ]

[4] V. Hatzivassiloglous and K. R. McKeown, "Predicting the semantic orientation of adjectives," Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, pp. 174–181, 1997.         [ Links ]

[5] P. D. Turney and M. L. Littman, "Measuring praise and criticism: Inference of semantic orientation from association," ACM Trans. Inf. Syst., vol. 21, no. 4, pp. 315–346, 2003.         [ Links ]

[6] J. Kamps and M. Marx, "Words with attitude," 1st International WordNet Conference, pp. 332–341, 2002.         [ Links ]

[7] S. Kim and E. Hovy, "Determining the sentiment of opinions," COLING 04: Proceedings of the 20th international conference on Computational Linguistics, pp. 1267–1373, 2004.         [ Links ]

[8] A. Esuli and F. Sebastiani, "Determining the semantic orientation of terms through gloss classification," CIKM '05: Proceedings of the 14th ACM international conference on Information and knowledge management, pp. 617–624, 2005.         [ Links ]

[9] A. Andreevskaia and S. Bergler, "Mining wordnet for a fuzzy sentiment: Sentiment tag extraction from wordnet glosses," Proceedings of the 11rd Conference of the European Chapter of the Association for Computational Linguistics (EACL–2006), pp. 209–216, 2006.         [ Links ]

[10] E. Riloff, J. Wiebe, and W. Phillips, "Exploiting subjectivity classification to improve information extraction," in Proc. of the NCAI, vol. 20, 2005, p. 1106.         [ Links ]

[11] J. Wiebe, T. Wilson, and C. Cardie, "Annotating expressions of opinions and emotions in language," in Language Resources and Evaluation, 2005, pp. 165–210.         [ Links ]

[12] A. Esuli and F. Sebastiani, "Determining term subjectivity and term orientation for opinion mining," EACL 2006, 11st Conference of the European Chapter of the Association for Computational Linguistics, pp. 193–200, 2006.         [ Links ]

[13] H. Kanayama and T. Nasukawa, "Fully automatic lexicon expansion for domain–oriented sentiment analysis," EMNLP 06: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing, pp. 355–363, 2006.         [ Links ]

[14] P. D. Turney, "Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews," ACL '02: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 417–424, 2004.         [ Links ]

[15] B. Pang and L. J. Lee, "A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts," ACL 04: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, pp. 271–278, 2004.         [ Links ]

[16] K. Dave, S. Lawrence, and D. M. Pennock, "Mining the peanut gallery: opinion extraction and semantic classification of product reviews," WWW '03: Proceedings of the 12th international conference on World Wide Web, pp. 519–528, 2003.         [ Links ]

[17] A. B. Goldberg and X. Zhu, "Seeing stars when there aren't many stars: graph–based semi–supervised learning for sentiment categorization," TextGraphs '06: Proceedings of TextGraphs: the First Workshop on Graph Based Methods for Natural Language Processing on the First Workshop on Graph Based Methods for Natural Language Processing, pp. 45–52, 2006.         [ Links ]

[18] K. Shimada and T. Endo, "Seeing several stars: A rating inference task for a document containing several evaluation criteria," PAKDD 2008: Proceedings of Advances in Knowledge Discovery and Data Mining, 12th Pacific–Asia Conference, pp. 1006–1014, 2008.         [ Links ]

[19] S. Baccianella, A. Esuli, and F. Sebastiani, "Multi–facet rating of product reviews," ECIR 09: Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval, pp. 461–472, 2009.         [ Links ]

[20] C. Strapparava and A. Valitutti, "WordNet–Affect: an affective extension of WordNet," LREC '04: Proceedings of the 4th International Conference on Language Resources and Evaluation, vol. 4, pp. 1083–1086, 2004.         [ Links ]

[21] C. Strapparava and R. F. Mihalcea, "Semeval–2007 task 14: affective text," SemEval '07: Proceedings of the 4th International Workshop on Semantic Evaluations, pp. 70–74, 2007.         [ Links ]

[22] A. Balahur and A. Montoyo, "Applying a culture dependent emotion triggers database for text valence and emotion classification," Procesamiento del lenguaje natural, vol. 40, pp. 107–114, 2008.         [ Links ]

[23] C. Strapparava and R. Mihalcea, "Learning to identify emotions in text," SAC 08: Proceedings of the 2008 Association for Computational Linguistics Symposium on Applied Computing, pp. 1556–1560, 2008.         [ Links ]

[24] S. Kim and E. Hovy, "Identifying opinion holders for question answering in opinion texts," Proc. of AAAI Workshop on Question Answering in Restricted Domains, 2005.         [ Links ]

[25] N. S. Glance, M. Hurst, and T. Tomokiyo, "Blogpulse: Automated trend discovery for weblogs," WWW 2004 Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics, 2004.         [ Links ]

[26] M. Platakis, D. Kotsakos, and D. Gunopulos, "Discovering hot topics in the blogosphere," in Proc. of the Panhellenic Scientific Student Conference on Informatics, Related Technologies and Applications EUREKA, 2008, pp. 122–132.         [ Links ]

[27] K. E. Gill, "How can we measure the influence of the blogosphere?" WWW 2004 Workshop on the Weblogging Ecosystem: Aggregation, Analysis and Dynamics, 2004.         [ Links ]

[28] A. Java, P. Kolari, T. Finin, and T. Oates, "Modeling the spread of influence on the blogosphere," Proceedings of the 15th International World Wide Web Conference, 2006.         [ Links ]

[29] A. Kale, "Modeling trust and influence in the blogosphere using link polarity," ICWSM 07: Proceedings of the International Conference on Weblogs and Social Media, 2007.         [ Links ]

[30] M. Hu and B. Liu, "Mining and summarizing customer reviews," KDD 04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 168–177, 2004.         [ Links ]

[31] L. Zhao and C. Li, "Ontology based opinion mining for movie reviews," in Proc. of KSEM, 2009, pp. 204–214.         [ Links ]

[32] P. Shvaiko, "Iterative schema based semantic matching," in PhD–Thesis, International Doctorate School in Information and Communication Technology, 2006, univ. Trento, Italia.         [ Links ]

[33] S. Castano, V. De Antonellis, and S. De Capitani di Vimercati, "Global viewing of heterogeneous data sources," IEEE Trans. on Knowl. and Data Eng., vol. 13, no. 2, pp. 277–297, 2001.         [ Links ]

[34] H.–H. Do and E. Rahm, "COMA: A system for flexible combination of schema matching approaches," VLDB '02: Proceedings of the 28th international conference on Very Large Data Bases, pp. 610–621, 2002.         [ Links ]

[35] J. Madhavan, P. A. Bernstein, and E. Rahm, "Generic Schema Matching with Cupid," VLDB '01: Proceedings of the 27th International Conference on Very Large Data Bases, pp. 49–58, 2001.         [ Links ]

[36] S. Melnik, H. Garcia–Molina, and E. Rahm, "Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching," ICDE 02: Proceedings of the 18th International Conference on Data Engineering, p. 117, 2002.         [ Links ]

[37] A. Doan, J. Madhavan, R. Dhamankar, P. Domingos, and A. Halevy, "Learning to match ontologies on the semantic web," The VLDB Journal, vol. 12, no. 4, pp. 303–319, 2003.         [ Links ]

[38] M. Ehrig and S. Staab, "Qom – quick ontology matching," pp. 683–697, 2004.         [ Links ]

[39] J. Euzenat, P. Gugan, and P. Valtchev, "OLA in the OAEI 2005 alignment contest," Proceedings of the K–CAP Workshopon Integrating Ontologies, pp. 61–71, 2005.         [ Links ]

[40] F. Giunchiglia, P. Shvaiko, and M. Yatskevich, "S–match: an algorithm and an implementation of semantic matching," in Proc. of ESWS 2004, Y. Kalfoglou and et al., Eds. Springer, 2004, pp. 61–75.         [ Links ]

[41] B. Le, R. Dieng–Kuntz, and F. Gandom, "On ontology matching problems – for building a corporate semantic web in a multi–communities organization," in Proc. of the Sixth International Conference on Enterprise Information Systems, no. 4, Abril 2004, pp. 236–243.         [ Links ]

[42] N. Noy and M. Musen, "The PROMPT suite: interactive tools for ontology merging and mapping," International Journal of Human–Computer Studies, vol. 59, no. 6, pp. 983–1024, 2003.         [ Links ]

[43] K. Kotis, G. Vouros, and K. Stergiou, "Capturing semantics towards automatic coordination of domain ontologies," in the 11th International conference of Artificial Intelligence: Methodology, Systems, Architectures – Semantic Web Challenges – AIMSA 2004. Springer–Verlag, 2004, pp. 22–32.         [ Links ]

[44] P. Lambrix and H. Tan, "SAMBO–A system for aligning and merging biomedical ontologies," Web Semant., vol. 4, no. 3, pp. 196–206, 2006.         [ Links ]

[45] Y. Qu, W. Hu, and G. Cheng, "Constructing virtual documents for ontology matching," in WWW 06: Proceedings of the 15th international conference on World Wide Web, 2006, pp. 23–31.         [ Links ]

[46] N. F. Noy, "Semantic integration: a survey of ontology–based approaches," SIGMOD Rec., vol. 33, no. 4, pp. 65–70, 2004.         [ Links ]

[47] E. Rahm and P. A. Bernstein, "A survey of approaches to automatic schema matching," The VLDB Journal, vol. 10, no. 4, pp. 334–350, 2001.         [ Links ]

[48] C. Phytila, "An Analysis of the SUMO and Description in Unified Modeling Language," 2002, no publicado.         [ Links ]

[49] S. Semy, M. Pulvermacher, and L. Obrst, "Toward the use of an upper ontology for U.S. government and U.S. military domains: An evaluation," in Submission to Workshop on IIWeb, 2004.         [ Links ]

[50] A. Kiryakov, K. Simov, and M. M. Dimitrov, "Ontomap: portal for upper–level ontologies," in Proc. of the FOIS. ACM, 2001, pp. 47–58.         [ Links ]

[51] P. Grenon, B. Smith, and L. Goldberg, "Biodynamic ontology: applying BFO in the biomedical domain," in Ontologies in Medicine, D. M. Pisanelli, Ed. IOS Press, 2004, pp. 20–38.         [ Links ]

[52] D. Lenat and R. Guha, Building Large Knowledge–Based Systems; Representation and Inference in the Cyc Project. Boston, MA, USA: Addison–Wesley Longman Publishing Co., Inc., 1989.         [ Links ]

[53] A. Gangemi, N. Guarino, C. Masolo, A. Oltramari, and L. Schneider, "Sweetening ontologies with DOLCE," in Proc. of EKAW. Springer, 2002, pp. 166–181.         [ Links ]

[54] H. Herre, B. Heller, P. Burek, R. Hoehndorf, F. Loebe, and H. Michalek, "General formal ontology (GFO): A foundational ontology integrating objects and processes. Part I: Basic principles," Research Group Ontologies in Medicine (Onto–Med), Univ. Leipzig, Tech. Rep. Nr. 8, 2006.         [ Links ]

[55] N. Casellas, M. Blzquez, A. Kiryakov, P. Casanovas, M. Poblet, and V. Benjamins, "OPJK into PROTON: Legal domain ontology integration into an upper–level ontology," in Proc. of WORM 2005. Springer, 2005, pp. 846–855.         [ Links ]

[56] J. Sowa, Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks Cole Publishing, 2000.         [ Links ]

[57] I. Niles and A. Pease, "Towards a standard upper ontology," in FOIS 01: Proceedings of the international conference on Formal Ontology in Information Systems. New York, NY, USA: ACM, 2001, pp. 2–9.         [ Links ]

[58] V. Mascardi, V. Cord, and P. Rosso, "A comparison of upper ontologies," in Atti del Workshop Dagli Oggentti agli Agenti, WOA, M. Baldoni and et al., Eds. Seneca Editore, 2007, pp. 55–64.         [ Links ]

[59] G. Stoilos, G. Stamou, and S. Kollias, "A string metric for ontology alignment," in Proc. of the ISWC, 2005, pp. 624–637.         [ Links ]

[60] V. Levenshtein, "Binary codes capable of correcting deletions, insertions, and reversals," Soviet Physics Doklady, vol. 10, no. 8, pp. 707–710, 1966.         [ Links ]

[61] V. Mascardi, A. Locoro, and P. Rosso, "Automatic ontology matching via upper ontologies: A systematic evaluation," IEEE Transactions on Knowledge and Data Engineering, vol. 99, no. 1, 2009, doi: 10.1109/TKDE.2009.154.         [ Links ]

[62] A. Locoro, "Ontology Matching using Upper Ontologies and Natural Language Processing," in PhD–Thesis Course in Electronic and Computer Engineering, Robotics and Telecommunications, 2010, univ. Genova, Italia.         [ Links ]

[63] A. Utsumi, "A unified theory of irony and its computational formalization," Proceedings of the 16th conference on Computational linguistics, pp. 962–967, 1996.         [ Links ]

[64] A. Reyes, P. Rosso, and D. Buscaldi, "Humor in the blogosphere: First clues for a verbal humor taxonomy," Journal of Intelligent Systems, vol. 18, no. 4, 2009.         [ Links ]