Clustering of Authors’ Texts of English Fiction in the Vector Space of Semantic Fields
References
- 1. Deerwester, S., S. T. Dumais, G. W. Furnas, T.K. Landauer, R. Harshman.Indexing by Latent Semantic Analysis. - Journal of the American Society for Information Science, Vol. 41, 1990, 391-407.
- 2. Fellbaum, C. WordNet. An Electronic Lexical Database. Cambridge, MA, MIT Press, 1998.
- 3. Gliozzo, A., C. Strapparava . Semantic Domains in Computational Linguistics. Springer, 2009.
- 4. Larsen, B., C. Aone. Fast and Effective Text Mining Using Linear-Time Document Clustering. - In: Proc. of 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’99), ACM, New York, 1999, 16-22.
- 5. Manning, C.D., P. Raghavan, H. Schütze. Introduction to Information Retrieval. Cambridge University Press, 2008.
- 6. Pantel, P., P.D.Turney, From Frequency to Meaning: Vector Space Models of Semantics. - Journal of Artificial Intelligence Research, Vol. 37, 2010, 141-188.
- 7. Sebastiani, F. Machine Learning in Automated Text Categorization. - ACM Computing Surveys. Vol. 34, 2002, 1-47.
- 8. Shehata, S., F. Karray, M. Kamel. Enhancing Text Clustering Using Concept-Based Mining Model. - In: Proc of Data Mining, ICDM’ 06, 6th International Conference, Waterloo, 2006, 1043-1048.
DOI: https://doi.org/10.2478/cait-2014-0030 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702 (formerly 1314-4081)
Language: English
Page range: 25 - 36
Published on: Nov 5, 2014
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Keywords:
Related subjects:
© 2014 Bohdan Pavlyshenko, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.