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Text Mining pp 79-99 | Cite as

Text Categorization: Conceptual View

  • Taeho Jo
Chapter
Part of the Studies in Big Data book series (SBD, volume 45)

Abstract

This chapter is concerned with the conceptual view of text categorization.

References

  1. 6.
    Boiy, E., Moens, M.F.: A machine learning approach to sentiment analysis in multilingual Web texts. Inf. Retr. 12, 525–558 (2009)Google Scholar
  2. 10.
    Clark, J., Koprinska, I., Poon, J.: A neural network based approach to automated e-mail classification. In: Proceedings of IEEE/WIC International Conference on Web Intelligence, pp. 702–705 (2003)Google Scholar
  3. 15.
    Dumais, S., Chen, H.: Hierarchical classification of Web content. In: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 256–263 (2000)Google Scholar
  4. 17.
    Fall, C.J., Torcsvari, A., Benzineb, K., Karetka, G.: Automated categorization in the international patent classification. ACM SIGIR Forum 37, 10–25 (2003)Google Scholar
  5. 20.
    Hanani, U., Shapira, B., Shoval, P.: Information filtering: overview of issues, research and systems. User Model. User-Adap. Inter. 11, 203–259 (2001)Google Scholar
  6. 25.
    Jo, T.: The Implementation of Dynamic Document Organization Using the Integration of Text Clustering and Text Categorization, University of Ottawa (2006)Google Scholar
  7. 45.
    Jo, T., Seo, J., Kim, H.: Topic spotting on news articles with topic repository by controlled indexing. Lect. Note Comput. Sci. 1983, 386–391 (2000)Google Scholar
  8. 56.
    Kroon, H.C.M.D., Kerckhoffs, E.J.H.: Improving learning accuracy in information filtering. In: International Conference on Machine Learning-Workshop on Machine Learning Meets HCI (1996)Google Scholar
  9. 60.
    Liu, J., Chua, T.S.: Building semantic perceptron net for topic spotting. In: Proceedings of the 39th Annual Meeting on Association for Computational Linguistics, pp. 378–385 (2001)Google Scholar
  10. 62.
    Loredana, F., Lemnaru, C., Potolea, R.: Spam detection filter using KNN algorithm and resampling. In: Proceedings of IEEE International Conference on Intelligent Computer Communication and Processing, pp. 27–33 (2010)Google Scholar
  11. 64.
    Maas, A.L., Daly, R.E., Pham, P.T., Huang, D., Ng, A.V., Potts, C.: Learning word vectors for sentiment analysis. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, vol. 1, pp. 142–150 (2011)Google Scholar
  12. 71.
    Mullen, T., Collier, N.: Sentiment analysis using support vector machines with diverse information sources. In: Proceedings of Conference on Empirical Methods in Natural Language Processing, pp. 412–418 (2004)Google Scholar
  13. 72.
    Myers, K., Kearns, M., Singh, S., Walker M.A.: A boosting approach to topic spotting on subdialogues. Family Life 27, 1 (2000)Google Scholar
  14. 75.
    Pang, B., Lee, L.: Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2, 1–135 (2008)Google Scholar
  15. 84.
    Schneider, K.M.: A comparison of event models for Naive Bayes anti-spam e-mail filtering. In: Proceedings of the Tenth Conference on European Chapter of the Association for Computational Linguistics, pp. 307–314 (2003)Google Scholar
  16. 87.
    Shardanand, U., Maes, P.: Social information filtering: algorithms for automating word of mouth. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 210–217 (1995)Google Scholar
  17. 88.
    Sriram, B., Fuhry, D., Demir, E.: Ferhatosmanoglu, H., Demirbas, M.: Short text classification in twitter to improve information filtering. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 441–442 (2010)Google Scholar
  18. 95.
    Wiener, E.D.: A neural network approach to topic spotting in text. The Master Thesis of University of Colorado (1995)Google Scholar
  19. 100.
    Youn, S., McLeod, D.: A comparative study for email classification. In: Advances and Innovations in Systems, Computing Sciences and Software Engineering, pp. 387–391 (2007)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Taeho Jo
    • 1
  1. 1.School of Game, Hongik UniversitySeoulKorea (Republic of)

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