Similar Text Fragments Extraction for Identifying Common Wikipedia Communities
1
Department of Intelligent Computer Systems, National Technical University “Kharkiv Polytechnic Institute”, 61002 Kharkiv, Ukraine
2
Department of Information Systems, Poznan University of Economics and Business, 61-875 Poznan, Poland
3
Institute of Information and Computational Technologies, Almaty 050010, Kazakhstan
4
Department of Informatics, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
*
Authors to whom correspondence should be addressed.
Data 2018, 3(4), 66; https://doi.org/10.3390/data3040066
Received: 4 November 2018
/
Revised: 9 December 2018
/
Accepted: 10 December 2018
/
Published: 13 December 2018
(This article belongs to the Special Issue Data Stream Mining and Processing)
Similar text fragments extraction from weakly formalized data is the task of natural language processing and intelligent data analysis and is used for solving the problem of automatic identification of connected knowledge fields. In order to search such common communities in Wikipedia, we propose to use as an additional stage a logical-algebraic model for similar collocations extraction. With Stanford Part-Of-Speech tagger and Stanford Universal Dependencies parser, we identify the grammatical characteristics of collocation words. With WordNet synsets, we choose their synonyms. Our dataset includes Wikipedia articles from different portals and projects. The experimental results show the frequencies of synonymous text fragments in Wikipedia articles that form common information spaces. The number of highly frequented synonymous collocations can obtain an indication of key common up-to-date Wikipedia communities.
View Full-Text
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Petrasova, S.; Khairova, N.; Lewoniewski, W.; Mamyrbayev, O.; Mukhsina, K. Similar Text Fragments Extraction for Identifying Common Wikipedia Communities. Data 2018, 3, 66. https://doi.org/10.3390/data3040066
AMA Style
Petrasova S, Khairova N, Lewoniewski W, Mamyrbayev O, Mukhsina K. Similar Text Fragments Extraction for Identifying Common Wikipedia Communities. Data. 2018; 3(4):66. https://doi.org/10.3390/data3040066
Chicago/Turabian StylePetrasova, Svitlana, Nina Khairova, Włodzimierz Lewoniewski, Orken Mamyrbayev, and Kuralay Mukhsina. 2018. "Similar Text Fragments Extraction for Identifying Common Wikipedia Communities" Data 3, no. 4: 66. https://doi.org/10.3390/data3040066
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
