The Linguometric Approach for Co-authoring Author's Style Definition

The linguometry technologies for determining the author's style of publications are applied. The statistical linguistic analysis of the author's text allows to use the benefits of content-monitoring of text using Stemming Algorithms or Stemmer by Martin F. Porter and NLP methods to determine the set of stop words. They are used in linguometric methods for calculation of text diversity coefficients with the aim to determine the degree of attribution of the text to the specific author. A formal approach to the author's style definition for Ukrainian-language texts is proposed. The experimental results of the developed method for determining the degree of authorship attribution of the analyzed text to specific author are obtained if a another author's text fragment is provided as reference. The experimental research was carried out using technical Ukrainian-language texts.

[1]  Vasyl Lytvyn,et al.  Development of a method for the recognition of author’s style in the Ukrainian language texts based on linguometry, stylemetry and glottochronology , 2017 .

[2]  Vasyl Lytvyn,et al.  Development of a method for determining the keywords in the slavic language texts based on the technology of web mining , 2017 .

[3]  Olga Lozynska,et al.  Information system for translation into ukrainian sign language on mobile devices , 2017, 2017 12th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT).

[4]  Olga Lozynska,et al.  Mathematical Method of Translation into Ukrainian Sign Language Based on Ontologies , 2017 .

[5]  Petro Kravets,et al.  The control agent with fuzzy logic , 2010, 2010 Proceedings of VIth International Conference on Perspective Technologies and Methods in MEMS Design.

[6]  P. Kravets,et al.  The Game Method for Orthonormal Systems Construction , 2007, 2007 9th International Conference - The Experience of Designing and Applications of CAD Systems in Microelectronics.

[7]  Bamshad Mobasher,et al.  Data Mining for Web Personalization , 2007, The Adaptive Web.

[8]  Yevhen Burov,et al.  Information resources processing using linguistic analysis of textual content , 2017, 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS).

[9]  Victoria Vysotska,et al.  Linguistic analysis of textual commercial content for information resources processing , 2016, 2016 13th International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET).

[10]  Taras Basyuk The main reasons of attendance falling of internet resource , 2015, 2015 Xth International Scientific and Technical Conference "Computer Sciences and Information Technologies" (CSIT).

[11]  Lyubomyr Chyrun,et al.  The commercial content digest formation and distributional process , 2016, 2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT).

[12]  Vasyl Lytvyn,et al.  Content linguistic analysis methods for textual documents classification , 2016, 2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT).

[13]  Olga Lozynska,et al.  Linguistic models of assistive computer technologies for cognition and communication , 2016, 2016 XIth International Scientific and Technical Conference Computer Sciences and Information Technologies (CSIT).

[14]  Gregory Piatetsky-Shapiro,et al.  Web Content Mining , 2009, Encyclopedia of Database Systems.

[15]  Di Cai,et al.  Sentiment Analysis of Polish Texts , 2012 .

[16]  Vasyl Lytvyn,et al.  The method of formation of the status of personality understanding based on the content analysis , 2016 .

[17]  Vasyl Lytvyn The similarity metric of scientific papers summaries on the basis of adaptive ontologies , 2011, Perspective Technologies and Methods in MEMS Design.

[18]  Anjali Ganesh Jivani,et al.  A Comparative Study of Stemming Algorithms , 2011 .