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Abstract
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.
Authors (3)
-
Mariia Rizun magistr
- University of Economics in Katowice, Poland,
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- THE SECOND CONFERENCE ON INNOVATIVE TEACHING METHODS (ITM 2017) strony 180 - 194
- Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- 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
- Verified by:
- Gdańsk University of Technology
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