ITM Web Conf.
Volume 18, 20187th Seminar on Industrial Control Systems: Analysis, Modeling and Computing (ICS 2018)
|Number of page(s)||6|
|Published online||09 April 2018|
Soft clustering method for text mining, with an opportunity to attribute them to different semantic groups
Moscow Technological University (MIREA), 119454 Moscow, Russia
* Corresponding author: firstname.lastname@example.org
The work describes new soft clustering method for text mining, developed by the authors, with an opportunity to attribute them to different semantic groups. The work of this algorithm is based on usage of definition parameter, when deterimining clustering accuracy, which can be defined for texts of various subject areas either on basis of percolation properties of text clusters, or estimated theoretically based on the redundancy model for text messages. By the author’s assumption, proposed algorithm must have speed and accuracy for clustering of texts, depending on value of clustering accuracy parameter. The advantage of this algorithm is that no need to set an initial value of clusters.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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