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SEMANTIC ANALYSIS ALGORITHMS FOR KNOWLEDGE WORKERS SUPPORT

Abstrakt

The paper examines various aspects of text analysis application for knowledge worker’s activity realization. Conclusions are drawn about the relevance and importance of processing the non-structured textual information in order to increase knowledge worker’s efficiency, as well as their awareness in different branches of science. The paper considers the existing algorithms of texts semantic analysis as the sphere of documents topical closeness recognition. At the same time, it contains an example of applying the complex methodology of semantic analysis, which includes LSA and LDA methods together with the Zipf’s Law with the objective to solve a typical knowledge worker’s task. Quantitative identifiers of the efficiency of this methodology are given.

Informacje szczegółowe

Kategoria:
Aktywność konferencyjna
Typ:
publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
Tytuł wydania:
THE SECOND CONFERENCE ON INNOVATIVE TEACHING METHODS (ITM 2017) strony 180 - 194
Język:
angielski
Rok wydania:
2017
Opis bibliograficzny:
Rizun N., Rizun M., Taranenko J.: SEMANTIC ANALYSIS ALGORITHMS FOR KNOWLEDGE WORKERS SUPPORT// THE SECOND CONFERENCE ON INNOVATIVE TEACHING METHODS (ITM 2017)/ Varna: , 2017, s.180-194
Bibliografia: test
  1. Bahl L., Baker, J., Jelinek E. & Mercer, R. (1977) Perplexity -a Measure of the Difficulty of Speech Recognition Tasks. In Program, 94th Meeting of the Acoustical Society of America, volume 62, page S63.
  2. Baker, J.C. (1998) A Test of Authorship Based on the Rate at which New Words Enter an Author's Text. Journal Article published 1 Jan 1988 in Literary and Linguistic Computing, volume 3, issue 1, pp. 36-39. otwiera się w nowej karcie
  3. Blei, D. M. (2012) Introduction to Probabilistic Topic Models. Comm. ACM 55 (4), April, 2012: pp. 77-84 otwiera się w nowej karcie
  4. Blei, D. M., Ng, A. & Jordan, M. (2003) Latent Dirichlet Allocation. Journal of Machine Learning Research, 3: pp. 993-1022. otwiera się w nowej karcie
  5. Bose, R. P. J. C. & and van der Aalst, W. M. P. (2009) Context Aware Trace Clustering: Towards Improving Process Mining Results. In SIAM International Conference on Data Mining, pages 401-412. otwiera się w nowej karcie
  6. Cantú, F.J. & Ceballos, H.G. (2010) A Multiagent Knowledge and Information Network Approach for Managing Research Assets. Expert Systems with Applications, 37(7), 5272-5284. doi:10.1016/j.eswa.2010.01.012 otwiera się w nowej karcie
  7. Cheng, H., Lu, Y. & Sheu, C. (2009) An Ontology-Based Business Intelligence Application in a Financial Knowledge Management System. Expert Systems with Applications, 36, 3614-3622. Doi:10.1016/j.eswa.2008.02.047 otwiera się w nowej karcie
  8. Deerwester, S., Dumais, S. T. & Harshman, R. (1990) Indexing by Latent Semantic Analysis. http://lsa.colorado.edu/papers/JASIS.lsi.90.pdf
  9. Dempster, A.P., Laird, N.M. & Rubin, D.B. (1977) Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society. Series B., Vol. 39. No 1, pp. 1-38 otwiera się w nowej karcie
  10. Dumais, S. T., Furnas, G. W., Landauer, T. K. & Deerwester, S. (1988) Using Latent Semantic Analysis to Improve Information Retrieval. In Proceedings of CHI'88: Conference on Human Factors in Computing, New York: ACM, 281-285 otwiera się w nowej karcie
  11. Ghattas, J., Peleg, M., Soffer, P., & Denekamp, Y. (2010) Learning the Context of a Clinical Process. In Business Process Management Workshops, pages 545-556. Springer. otwiera się w nowej karcie
  12. Gomez-Perez, J. M., Grobelnik, M., Ruiz, C., Tilly, M., & Warren, P. (2009) Using Task Context to Achieve Effective Information Delivery. In Proceedings of the 1st Workshop on Context, Information and Ontologies, pages 1-6. ACM. otwiera się w nowej karcie
  13. Hwang, H.G., Chang, I.C., Chen, F.J. & Wu, S.Y. (2008) Investigation of the Application of KMS for Diseases Classifications: A Study in a Taiwanese Hospital. Expert Systems with Applications, 34(1), 725-733. doi:10.1016/j.eswa.2006.10.018 otwiera się w nowej karcie
  14. Li, X., Zhu, Z. & Pan, X. (2010, a) Knowledge Cultivating for Intelligent Decision Making in Small & Middle Businesses. Procedia Computer Science, 1(1), 2479-2488. doi:10.1016/j.procs.2010.04.280 otwiera się w nowej karcie
  15. Li, Y., Kramer, M.R., Beulens, A.J.M. &Van Der Vorst, J.G.A.J. (2010, b) A Framework for Early Warning and Proactive Control Systems in Food Supply Chain Networks. Computers in Industry, 61, 852-862. Doi:101.016/j.compind.2010.07.010 otwiera się w nowej karcie
  16. Liao, S. (2003) Knowledge Management Technologies and Applications-Literature Review From 1995 to 2002. Expert Systems with Applications, 25, 155-164. doi:10.1016/S0957-4174(03)00043-5 otwiera się w nowej karcie
  17. Liao, S.H., Chen, C.M. and Wu, C.H. (2008) Mining Customer Knowledge for Product Line and Brand Extension in Retailing. Expert Systems with Applications, 34(3), 1763- 1776. doi:10.1016/j.eswa.2007.01.036 otwiera się w nowej karcie
  18. Liu, D.R. & Lai, C.H. (2011) Mining Group-Based Knowledge Flows for Sharing Task Knowledge. Decision Support Systems,50(2), 370-386. doi:10.1016/j.dss.2010.09.004 otwiera się w nowej karcie
  19. McInerney, C. (2002) Knowledge Management and the Dynamic Nature of Knowledge. Journal of the American Society for Information Science and Technology, 53(12), 1009-1018. doi:10.1002/asi.10109 otwiera się w nowej karcie
  20. MIGnews.com.ua (2009) Authorship of writers can be learned by a special formula, http://mignews.com.ua/science/nauka/2531956.html otwiera się w nowej karcie
  21. Nokel, M. A. & Lukashevich, N.V. (2015) Thematic Models: Adding Bigrams and Accounting Similarities Between Unigrams and Bigrams. Computational methods and programming. Vol. 16, pp. 215-217 otwiera się w nowej karcie
  22. Nosenko, S. V, Korolev, I. D. & Poddubny, M.I. (2005) The Method of Automatic Classification Formalized Documents in the System of Electronic Document Management, MKK G06F17 / 30 otwiera się w nowej karcie
  23. Rizun, M. (2017a) Maturity Models as the Element of Knowledge Management Development. Materials of the Conference "Current Issues Raised by Young Researchers, X". CreativeTime, Krakow. ISBN 9788363058-71-5. Pp. 293 -298.
  24. Rizun, M. (2017b) Software Solutions for Knowledge Workers. Proceedings of the 2nd International Conference on Information Technologies in Management, Publisher: Rocznik Naukowy Wydziału Zarządzania WSM, http://www.wsmciechanow.edu.pl/rocznik-naukowy/ (in print).
  25. Rizun, N. & Taranenko, Y. (2017) Development of the Algorithm of Polish Language Film Reviews Preprocessing. Proceeding of the 2nd International Conference on Information Technologies in Management, Publisher: Rocznik Naukowy Wydziału Zarządzania WSM, http://www.wsmciechanow.edu.pl/rocznik-naukowy/ (in print).
  26. Rizun, N., Kapłanski, P. & Taranenko, Y. (2016a) Development and Research of the Text Messages Semantic Clustering Methodology. 2016, Third European Network Intelligence Conference, Publisher: ENIC, # 33, pp.180-187. otwiera się w nowej karcie
  27. Rizun, N., Kapłanski, P. & Taranenko, Y. (2016b) Method of a Two-Level Text-Meaning Similarity Approximation of the Customers' Opinions. Economic Studies -Scientific Papers. University of Economics in Katowice, Nr. 296/2016, pp.64-85. otwiera się w nowej karcie
  28. Silwattananusarn, T. & Tuamsuk, K. (2012) Data Mining and its Applications for Knowledge Management: A Literature Review from 2007 to 2012, International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.2, No.5, September 2012, pp.13-24 otwiera się w nowej karcie
  29. Stajner, T. & Mladenic, D. (2010) Modeling Knowledge Worker Activity. MLR: Workshop on Applications of Pattern Analysis. Workshop and Conference Proceedings 11 (2010), pp. 127-133.
  30. Vorontsov, K.V. & Potapenko, A.A. (2013) Modifications of the EM-algorithm for probabilistic Thematic modeling // Machine learning and data analysis. Vol. 1. No. 6, pp. 657-686 otwiera się w nowej karcie
  31. Wang, F. & Fan, H. (2008) Investigation on Technology Systems for Knowledge Management.IEEE, 1-4. doi:10.1109/WiCom.2008.2716 otwiera się w nowej karcie
  32. Wu, W., Lee, Y.T., Tseng, M.L. & Chiang, Y.H. (2010) Data Mining for Exploring Hidden Patterns Between KM and its Performance. Knowledge-Based Systems, 23, 397-401. doi:10.1016/j.knosys.2010.01.014 otwiera się w nowej karcie
Weryfikacja:
Politechnika Gdańska

wyświetlono 29 razy

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