Development and Research of the Text Messages Semantic Clustering Methodology - Publikacja - MOST Wiedzy

Wyszukiwarka

Development and Research of the Text Messages Semantic Clustering Methodology

Abstrakt

The methodology of semantic clustering analysis of customer’s text-opinions collection is developed. The author's version of the mathematical models of formalization and practical realization of short textual messages semantic clustering procedure is proposed, based on the customer’s text-opinions collection Latent Semantic Analysis knowledge extracting method. An algorithm for semantic clustering of the text-opinions is developed, the distinctive characteristics of which is the introduction of concepts and methods of identification point of reference in the scale of text-opinions collection closeness determination; instrument of the documents’ closeness degree identification; measure of similarity between pairs of documents. The version of quantitative evaluation of the clustering results is developed. The concepts of resolving power of the method of semantic clustering and level of the clustering procedure quality are proposed. Analysis of the specific features and the effectiveness level of various distance measures is conducted

Cytowania

  • 0

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Autorzy (3)

Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
materiały konferencyjne indeksowane w Web of Science
Tytuł wydania:
Third European Network Intelligence Conference: Proceedings strony 180 - 187
Język:
angielski
Rok wydania:
2016
Opis bibliograficzny:
Rizun N., Kapłański P., Yurii T..: Development and Research of the Text Messages Semantic Clustering Methodology, W: Third European Network Intelligence Conference: Proceedings, 2016, IEEE,.
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1109/enic.2016.034
Bibliografia: test
  1. Jonathan I. Maletic, Naveen Valluri. "Automatic Software Clustering via Latent Semantic Analysis". 14th IEEE ASE'99, Cocoa Beach FL, Oct. 12-15th, pp. 251-254 otwiera się w nowej karcie
  2. Jon Rune Paulsen, Heri Ramampiaro "Combining Latent Semantic Indexing and Clustering to Retrieve and Cluster Biomedical Information: A 2-step Approach". NIK-2009 conference.
  3. L. Jing, M. K. Ng, X. Yang, and J. Z. Huang. "A text clustering system based on k-means type subspace clustering and ontology". International Journal of Intelligent Technology, 1(2):91-103, 2006. otwiera się w nowej karcie
  4. D. Dobrowolski, P. Kaplanski, A. Marciniak, and Z. Lojewski, "Semantic OLAP with FluentEditor and Ontorion Semantic Excel Toolchain,"IARIA, vol. SEMAPRO 2015: The Ninth International Conference on Advances in Semantic Processing, 2015. [Online]. Available: https://www.thinkmind.org/index.php?view=article& articleid =semapro_2015_3_30_30051 otwiera się w nowej karcie
  5. P. Kapłanski and P. Weichbroth, "Cognitum Ontorion: Knowledge Representation and Reasoning System," in Position Papers of the 2015 Federated Conference on Computer Science and Information Systems, FedCSIS 2015, Lódz, Poland, September 13-16, 2015., 2015. doi: 10.15439/2015F17 , pp. 177-184. [Online]. Available: http://dx.doi.org/10.15439/2015F17 otwiera się w nowej karcie
  6. P. Kapłanski, "Controlled english interface for knowledge bases," Studia Informatica, vol. 32, no. 2A, pp. 485-494, 2011
  7. A. Wroblewska, P. Kaplanski, P. Zarzycki, and I. Lugowska, "Semantic Rules Representation in Controlled Natural Language in FluentEditor," in Human System Interaction (HSI), 2013 The 6th International Conference on. IEEE, 2013, pp. 90-96 otwiera się w nowej karcie
  8. Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R., "Indexing by Latent Semantic Analysis", Journal of the American Society for Information Science, 41, 1990, pp. 391- 407 otwiera się w nowej karcie
  9. A. Dasgupta, R. Kumar, P. Raghavan, and A. Tomkins. Variable latent semantic indexing. In ACM SIGKDD 2005, 2005. otwiera się w nowej karcie
  10. Scott C. Deerwester, Susan T. Dumais, Thomas K. Landauer, George W. Furnas, and Richard A. Harshman. Indexing by latent semantic analysis. Journal of the American Society of Information Science, 41(6):391-407, 1990
  11. Miles Efron. Eigenvalue-based model selection during latent semantic indexing: Research articles. J. Am. Soc. Inf. Sci. Technol., 56(9): pp 969-988, 2005 otwiera się w nowej karcie
  12. Ricardo Olmos , José A. LeónUsing, Inmaculada Escudero, Guillermo Jorge-Botana. "Latent semantic analysis to grade brief summaries: some proposals". Int. J. Cont. Engineering Education and Life-Long Learning, Vol. 21, Nos. 2/3, 2011 otwiera się w nowej karcie
  13. Foltz, P. W. "Latent semantic analysis for text-based research", Behavior Research Methods, Instruments and Computers, 1996, Vol. 28, No. 2, pp.197-202 otwiera się w nowej karcie
  14. Xuren Wang, Qiuhui Zheng. "Text Emotion Classification Research Based on Improved Latent Semantic Analysis Algorithm". Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) otwiera się w nowej karcie
  15. Dumis S, Fumas G, Landauer T et al. "Using Latent Semantic Analysis to Improve Access to Textual Information". Proceedings of Computer Human Interaction, 1988.217-285 otwiera się w nowej karcie
  16. Salton G, Wong A, Yang CS. "A Vector Space Model for Automatic Indexing". Communications of the ACM,1995,18(11) : pp 613-620. otwiera się w nowej karcie
  17. Dmitri Roussinov, J. Leon Zhao. Text Clustering and Summary Techniques for CRM Message Management. [Online]. Available: https://personal.cis.strath.ac.uk/dmitri.roussinov/Lim-Paper.pdf otwiera się w nowej karcie
  18. Lee C-H. "Learning inductive rules using hellinger measure". Applied Artificial Intelli-gence, Volume 13, Number 8, 1 December 1999 , pp. 743-762(20) otwiera się w nowej karcie
  19. Han, E., Karypis G., Kumar V. "Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification". 16th International Conference on Machine Learn-ing -Denver, 1999. -pp. 41-56 otwiera się w nowej karcie
  20. Koller D., Sahami M. Hierarchically classyffying documents using very few words // Koller D., Sahami M., Proc. ICML-97. Nashvilee, 1997, pp.170-176
Weryfikacja:
Politechnika Gdańska

wyświetlono 27 razy

Publikacje, które mogą cię zainteresować

Meta Tagi