Estimating the Quality of Articles in Russian Wikipedia Using the Logical-Linguistic Model of Fact Extraction
Nina Khairova , Włodzimierz Lewoniewski , Krzysztof Węcel
AbstractWe present the method of estimating the quality of articles in Russian Wikipedia that is based on counting the number of facts in the article. For calculating the number of facts we use our logical-linguistic model of fact extraction. Basic mathematical means of the model are logical-algebraic equations of the finite predicates algebra. The model allows extracting of simple and complex types of facts in Russian sentences. We experimentally compare the effect of the density of these types of facts on the quality of articles in Russian Wikipedia. Better articles tend to have a higher density of facts.
|Publication size in sheets||0.6|
|Book||Abramowicz Witold (eds.): Business Information Systems 20th International Conference, BIS 2017 Poznan, Poland, June 28–30, 2017 Proceedings, Lecture Notes in Business Information Processing, vol. 288, 2017, Springer, ISBN 978-3-319-59335-7, [978-3-319-59336-4], 352 p.|
|Keywords in English||Russian Wikipedia, Article quality, Fact extraction, Logical equations|
|ASJC Classification||; ; ; ; ;|
|Score||= 70.0, 25-03-2020, ChapterFromConference|
|Publication indicators||= 5|
|Citation count*||10 (2020-10-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.