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Developing a Fuzzy Knowledge Base and Filling It with Knowledge Extracted from Various Documents

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Artificial Intelligence and Soft Computing (ICAISC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10842))

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Abstract

The article describes the process of developing a fuzzy knowledge base. The content of the fuzzy knowledge base is the result of extracting knowledge from the set of documents by subject area. Set of documents consists of the wiki-resources, UML-diagrams, documents and source code of projects. Knowledge base based on the graph database Neo4j. An attempt to implement the mechanism of inference by the contents of a graph database was made. This mechanism is used to generate the screen forms of the user interface dynamically. The contexts allow representing the content of the fuzzy knowledge base in space and time. Each space context is assigned a linguistic label, for example, low, middle, high. This label determines the competence of the expert in the given subject area. Time contexts allow storing the history of the knowledge base content changes. It allows returning to a specific state of the contents of the knowledge base.

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Acknowledgments

The study was supported by the Ministry of Education and Science of the Russian Federation in the framework of the project No. 2.1182.2017/4.6. Development of methods and means for automation of production and technological preparation of aggregate-assembly aircraft production in the conditions of a multi-product production program.

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Authors and Affiliations

  1. Ulyanovsk State Technical University, Street Severny Venets 32, 432027, Ulyanovsk, Russian Federation

    Nadezhda Yarushkina, Vadim Moshkin, Aleksey Filippov & Gleb Guskov

Authors
  1. Nadezhda Yarushkina
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  2. Vadim Moshkin
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  3. Aleksey Filippov
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  4. Gleb Guskov
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Corresponding author

Correspondence to Aleksey Filippov .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Yarushkina, N., Moshkin, V., Filippov, A., Guskov, G. (2018). Developing a Fuzzy Knowledge Base and Filling It with Knowledge Extracted from Various Documents. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2018. Lecture Notes in Computer Science(), vol 10842. Springer, Cham. https://doi.org/10.1007/978-3-319-91262-2_70

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  • DOI: https://doi.org/10.1007/978-3-319-91262-2_70

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