Estimating the Quality of Articles in Russian Wikipedia Using the Logical-Linguistic Model of Fact Extraction

被引：8
|
作者：
Khairova, Nina [1 ]
Lewoniewski, Wlodzimierz [2 ]
Wecel, Krzysztof [2 ]
机构：
[1] Natl Tech Univ Kharkiv Polytech Inst, 2 Kyrpychova Str, UA-61002 Kharkov, Ukraine
[2] Poznan Univ Econ & Business, Al Niepodleglosci 10, PL-61875 Poznan, Poland
来源：
BUSINESS INFORMATION SYSTEMS (BIS 2017) | 2017年 / 288卷
关键词：
Russian Wikipedia; Article quality; Fact extraction; Logical equations;
D O I：
10.1007/978-3-319-59336-4_3
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
We 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.
引用
收藏
页码：28 / 40
页数：13
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