On text preprocessing for opinion mining outside of laboratory environments

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7669 LNCS, Issue , 2012, Pages 618-629

  Petz, Gerald ^a   Karpowicz, Michał ^a   Fürschuß, Harald ^a   Auinger, Andreas ^a   Winkler, Stephan M ^b   Schaller, Susanne ^b   Holzinger, Andreas ^c  

^a UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

^b UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

^c MEDICAL UNIVERSITY OF GRAZ   (Austria)

Author keywords

content extraction; Internet slang; language detection; Opinion mining; sentiment analysis; text mining; Web analytics

Indexed keywords

CONTENT EXTRACTION; LANGUAGE DETECTION; OPINION MINING; SENTIMENT ANALYSIS; TEXT MINING; WEB ANALYTICS;

INTERNET; NATURAL LANGUAGE PROCESSING SYSTEMS; SPEECH RECOGNITION;

DATA MINING;

EID: 84870375867     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-35236-2_62     Document Type: Conference Paper

References (49)

1. Alby, T.: Web 2.0. Konzepte, Anwendungen, Technologien, 3rd edn. Hanser, München (2008)
2. Nelles, O.: Nonlinear system identification: from classical approaches to neural networks and fuzzy models. Springer (2001)
3. Liu, B.: Web data mining. Exploring hyperlinks, contents, and usage data, 2nd edn. Data-centric systems and applications. Springer, Berlin (2008)
4. Steinecke, U., Straub, W.: Unstrukturierte Daten im Business Intelligence. Vorgehen, Ergebnisse und Erfahrungen in der praktischen Umsetzung. HMD - Praxis der Wirtschaftsinformatik 47(271), 91-101 (2010)
5. Guozheng, Z., Faming, Z., Fang, W., Jian, L.: Knowledge Creation in Marketing Based on Data Mining. In: International Conference on Intelligent Computation Technology and Automation (ICICTA), vol. 1, pp. 782-786 (2008)
6. Holzinger, A.: Weakly Structured Data in Health-Informatics. In: Proceedings of INTERACT 2011 International Conference on Human-Computer Interaction, Workshop: Promoting and Supporting Healthy Living by Design, pp. 5-7 (2011)
7. Holzinger, A.: On Knowledge Discovery and Interactive Intelligent Visualization of Biomedical Data. In: Proceedings of the 9th International Joint Conference on e-Business and Telecommunications (ICETE 2012), pp. IS9-IS20 (2012)
8. Holzinger, A., Geierhofer, R., Modritscher, F., Tatzl, R.: Semantic Information in Medical Information Systems: Utilization of Text Mining Techniques to Analyze Medical Diagnoses. Journal of Universal Computer Science 14(22), 3781-3795 (2008)
9. Maynard, D., Bontcheva, K., Rout, D.: Challenges in developing opinion mining tools for social media. In: Proceedings of @NLP can u tag #user-generated-content?! Workshop at LREC 2012, Istanbul, Turkey (May 2012)
10. Abbasi, A., Chen, H., Salem, A.: Sentiment analysis in multiple languages: Feature selection for opinion classification in Web forums. ACM Trans. Inf. Syst. 26(3), 12:1-12:34 (2008)
11. Yi, L., Liu, B.: Web page cleaning for web mining through feature weighting. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence, pp. 43-48. Morgan Kaufmann Publishers Inc., San Francisco (2003)
12. Gamon, M.: Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis. In: Proceedings of the 20th International Conference on Computational Linguistics (2004)
13. Kaiser, C.: Opinion Mining im Web 2.0 - Konzept und Fallbeispiel. HMD - Praxis der Wirtschaftsinformatik 46(268), 90-99 (2009)
14. Kim, S.-M., Hovy, E.: Determining the Sentiment of Opinions. In: Proceedings of 20th International Conference on Computational Linguistics, Geneva, Switzerland, pp. 1367-1373 (2004)
15. Nadali, S., Masrah, A.A.M., Rabiah, A.K.: Sentiment Classification of Customer Reviews Based on Fuzzy logic. In: Mahmood, A.K. (ed.) International Symposium in Information Technology (ITSim), pp. 1037-1044. IEEE (2010)
16. Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168-177 (2004)
17. Jindal, N., Liu, B.: Mining comparative sentences and relations. In: Proceedings of the 21st National Conference on Artificial Intelligence, vol. 2, pp. 1331-1336. AAAI Press (2006)
18. Hatzivassiloglou, V., Wiebe, J.: Effects of Adjective Orientation and Gradability on Sentence Subjectivity. In: Proceedings of the 18th Conference on Computational Linguistics, pp. 299-305 (2000)
19. Turney, P.D.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, Philadelphia, PA, USA, pp. 417-424 (2002)
20. Wiebe, J., Mihalcea, R.: Word Sense and Subjectivity. In: Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics, pp. 1065-1072 (2006)
21. Ding, X., Liu, B., Yu, P.S.: A Holistic Lexicon-Based Approach to Opinion Mining. In: International Conference on Web Search & Data Mining, Palo Alto, California, February 11-12. ACM, New York (2008)
22. Popescu, A.-M., Etzioni, O.: Extracting Product Features and Opinions from Reviews. In: Proceedings of Human Language Technology Conference, pp. 339-346 (2005)
23. Tong, S., Koller, D.: Support Vector Machine Active Learning with Applications to Text Classification. Journal of Machine Learning Research 2, 45-66 (2001)
24. Weisberg, S.: Applied linear regression, vol. 528. Wiley (2005)
25. Vapnik, V.: The nature of statistical learning theory. Springer (2000)
26. Witten, I., Frank, E.: Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann (2005)
27. Kreuzthaler, M., Bloice, M.D., Faulstich, L., Simonic, K.M., Holzinger, A.: A Comparison of Different Retrieval Strategies Working on Medical Free Texts. Journal of Universal Computer Science 17(7), 1109-1133 (2011)
28. Holzinger, A., Simonic, K.M., Yildirim, P.: Disease-disease relationships for rheumatic diseases Web-based biomedical textmining and knowledge discovery to assist medical decision making. In: IEEE COMPSAC, pp. 573-580 (2012)
29. Koza, J.: Genetic programming II: automatic discovery of reusable programs (1994)
30. Affenzeller, M., Wagner, S., Winkler, S.: Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications. Numerical Insights. Taylor & Francis (2009)
31. Bai, X.: Predicting consumer sentiments from online text. Decision Support Systems 50(4), 732-742 (2011)
32. Lin, C., He, Y.: Joint sentiment/topic model for sentiment analysis. In: Proceedings of the 18th ACM Conference on Information and Knowledge Management, pp. 375-384. ACM, New York (2009)
33. Faschang, P., Petz, G., Dorfer, V., Kern, T., Winkler, S.M.: An Approach to Mining Consumer's Opinion on the Web. In: 13th International Conference on Computer Aided Systems Theory, Eurocast 2011, pp. 37-39 (2011)
34. Faschang, P., Petz, G., Wimmer, M., Dorfer, V., Winkler, S.M.: Evaluation of Tools for Opinion Mining. In: EEE (ed.) Proceedings of the 2011 International Conference on E-Learning, E-Business, Enterprise Information Systems & E-Government, Las Vegas, pp. 3-9 (2011)
35. Schaller, S., Winkler, S.M., Dorfer, V., Petz, G., Fürschuß, H.: A Machine Learning Suite for Opinion Mining in Web. In: Proceedings of the 14th International Asia Pacific Conference on Computer Aided System Theory, IEEE APCast (2012)
36. Mihalcea, R., Banea, C., Wiebe, J.: Learning Multilingual Subjective Language via Cross- Lingual Projections. In: Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, pp. 976-983 (2007)
37. Benedetto, D., Caglioti, E., Loreto, V.: Language Trees and Zipping. Phys. Rev. Lett. 88(4), 48702 (2002), doi:10.1103/PhysRevLett.88.048702
38. Grefenstette, G.: Comparing two language identification schemes. In: Proceedings of the 3rd International Conference on Statistical Analysis of Textual Data (JADT 1995), pp. 263-268 (1995)
39. Řehůřek, R., Kolkus, M.: Language Identification on the Web: Extending the Dictionary Method. In: Gelbukh, A. (ed.) CICLing 2009. LNCS, vol. 5449, pp. 357-368. Springer, Heidelberg (2009)
40. Cavnar, W.B., Trenkle, J.M.: Trenkle: N-Gram-Based Text Categorization. In: Proceedings of SDAIR 1994, 3rd Annual Symposium on Document Analysis and Information Retrieval, pp. 161-175 (1994)
41. Dunning, T.: Statistical Identification of Language (1994)
42. Laender, A.H.F., Ribeiro-Neto, B.A., da Silva, A.S., Teixeira, J.S.: A brief survey of web data extraction tools. SIGMOD Rec. 31(2), 84-93 (2002), doi:10.1145/565117.565137
43. Weninger, T., Hsu, W.H.: Text Extraction from the Web via Text-to-Tag Ratio. In: Proceedings of the 2008 19th International Conference on Database and Expert Systems Application, pp. 23-28. IEEE Computer Society, Washington, DC (2008), doi:10.1109/DEXA.2008.12
44. Weninger, T., Hsu, W.H., Han, J.: CETR: content extraction via tag ratios. In: Proceedings of the 19th International Conference on World Wide Web, pp. 971-980. ACM, New York (2010), doi:10.1145/1772690.1772789
45. Pasternack, J., Roth, D.: Extracting article text from the web with maximum subsequence segmentation. In: Proceedings of the 18th International Conference on World Wide Web, pp. 971-980 (2009)
46. Kohlschütter, C., Fankhauser, P., Nejdl, W.: Boilerplate detection using shallow text features. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, pp. 441-450. ACM, New York (2010)
47. van Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworth-Heinemann, Newton, MA, USA (1979)
48. Baroni, M., Chantree, F., Kilgarriff, A., Sharoff, S.: Cleaneval: a Competition for Cleaning Web Pages
49. Schmid, H.: TreeTagger - a language independent part-of-speech tagger, http://www.ims.uni-stuttgart.de/projekte/corplex/TreeTagger/ (accessed March 10, 2011)