Methods for Structuring Knowledge in Online Encyclopedias
Abstract
Currently, several online encyclopedias are being developed in Russian. The Great Russian Encyclopedia, the Russian-language encyclopedia Ruwiki are being created. The "Ark of Knowledge" project is being developed at Lomonosov Moscow State University, which is considered as a repository of knowledge in various formats, as well as a base for preparing articles for the Great Russian Encyclopedia Internet-portal. Modern electronic encyclopedias include hundreds of thousands of articles. This requires the use of special means of structuring knowledge to improve the efficiency of information search and user navigation through the pages of the encyclopedia.
Hyperlinks are a generally accepted method of navigation between pages in online resources. Wikipedia, the largest and most famous Internet encyclopedia, has a developed system (hierarchy) of categories and subcategories, which unite Wikipedia pages into thematic groups. Similar categorization is used in a Russian Wikipedia-like resource - Ruwiki. The Great Russian Encyclopedia uses the system of facet classification and keywords.
The Lomonosov Moscow State University "Ark of Knowledge" system assumes the use of ontologies for structuring knowledge, i.e. formalized descriptions of subject areas in the form of a system of classes and relationships between them. Ontologies are supposed to improve the efficiency of information access, both for users and for automatic processing by software agents.
The article considers the features of each approach of knowledge structuring. In particular, the problems of the extensive Wikipedia category system created by users, which reflect typical difficulties in formalizing knowledge description, will be presented. The problems of using ontologies for knowledge categorization will be considered using Wikidata as an example.
References
2. Semenov A.L., Raevskij E.N., Bubnov A.S., Grishin I.Yu., Gulyaev A.V., Kobozeva I.M. Universal Encyclopedic Platform for Working with Knowledge. Modern Information Technologies and IT-Education. 2023;19(3):696-703. (In Russ., abstract in Eng.) https://doi.org/10.25559/SITITO.019.202303.696-703
3. Thornton K., McDonald D.W. Tagging Wikipedia: collaboratively creating a category system. In: Proceedings of the 2012 ACM International Conference on Supporting Group Work (GROUP '12). New York, NY, USA: Association for Computing Machinery; 2012. p. 219-228. https://doi.org/10.1145/2389176.2389210
4. Vrandečić D., Krötzsch M. Wikidata: a free collaborative knowledgebase. Communications of the ACM. 2014;57(10):78-85. https://doi.org/10.1145/2629489
5. Shenoy K., et al. A study of the quality of Wikidata. Journal of Web Semantics. 2022;72:100679. https://doi.org/10.1016/j.websem.2021.100679
6. Turki H., et al. Wikidata: A large-scale collaborative ontological medical database. Journal of biomedical informatics. 2019;99:103292. https://doi.org/10.1016/j.jbi.2019.103292
7. Faber P., León-Araúz P. From specialized knowledge frames to linguistically based ontologies. Applied Ontology. 2024;19(3):1-23. https://doi.org/10.3233/AO-230033
8. Hohenecker P., Lukasiewicz T. Ontology reasoning with deep neural networks. Journal of Artificial Intelligence Research. 2020;68:503-540. https://doi.org/10.1613/jair.1.11661
9. Baydaroğlu Ö., et al. A comprehensive review of ontologies in the hydrology towards guiding next generation artificial intelligence applications. Journal of Environmental Informatics. 2023;42(2):90-107. https://doi.org/10.3808/jei.202300500
10. Wróblewska A. et al. Methods and tools for ontology building, learning and integration application in the synat project. Intelligent tools for building a scientific information platform. 2012. p. 121-151. doi: https://doi.org/10.1007/978-3-642-24809-2_9
11. Loukachevitch N.V. Tezaurusy v zadachah informacionnogo poiska [Thesauri in information retrieval tasks]. Moscow: Moscow University Press; 2011. 512 p. (In Russ.) EDN: RBBMVR
12. Bates M.J. How to Use Controlled Vocabularies More Effectively in Online Searching. Online. 1988;12(6):45-56.
13. Davies J. Lightweight Ontologies. In: Poli R., Healy M., Kameas A. (eds.) Theory and Applications of Ontology: Computer Applications. Dordrecht: Springer; 2010. p. 197-229. https://doi.org/10.1007/978-90-481-8847-5_9
14. Janowicz K., et al. SOSA: A lightweight ontology for sensors, observations, samples, and actuators. Journal of Web Semantics. 2019;56:1-10. https://doi.org/10.1016/j.websem.2018.06.003
15. Olteanu-Raimond A.M., et al. A lightweight ontology for landmarks to assist rescue in mountainous areas. Advances in Cartography and GIScience of the ICA. 2023;4:15. https://doi.org/10.5194/ica-adv-4-15-2023
16. Guarino N. Some ontological principles for designing upper level lexical resources. In: First International Conference on language resources & evaluation: Granada, Spain, 28-30 May 1998. European Language Resources Association; 1998. p. 527-534. https://doi.org/10.48550/arXiv.cmp-lg/9809002
17. Loukachevitch N. Establishment of Taxonomic Relationships in Linguistic Ontologies. In: Wolff K.E., Palchunov D.E., Zagoruiko N.G., Andelfinger U. (eds.) Knowledge Processing and Data Analysis. KPP KONT 2007. Lecture Notes in Computer Science. Vol. 6581. Berlin, Heidelberg: Springer; 2011. p. 232-242. https://doi.org/10.1007/978-3-642-22140-8_15
18. Romanenko E., Calvanese D., Guizzardi G. Abstracting Ontology-Driven Conceptual Models: Objects, Aspects, Events, and Their Parts. In: Guizzardi R., Ralyté J., Franch X. (eds.) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing. Vol. 446. Cham: Springer; 2022. p. 372-388. https://doi.org/10.1007/978-3-031-05760-1_22
19. Loukachevitch N.V. Part-whole relations in theory and practice. Neurocomputers. 2013;(1):007-012. EDN: PVRZNN
20. Kravec S.L. Scientific and educational encyclopedic portal and participation of regional scientific encyclopedias in it. Voprosy ehnciklopedistiki. 2019;(2):14-20. (In Russ., abstract in Eng.) EDN: NPZYHS
21. Vivaldi J., Rodríguez H. Finding Domain Terms using Wikipedia. In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10). Valletta, Malta: European Language Resources Association; 2010. p. 386-393. Available at: https://aclanthology.org/L10-1518/ (accessed 21.05.2024).
22. Bordea G., et al. Evaluation Dataset and Methodology for Extracting Application-Specific Taxonomies from the Wikipedia Knowledge Graph. In: Proceedings of the Twelfth Language Resources and Evaluation Conference. Marseille, France: European Language Resources Association; 2020. p. 2341-2347. Available at: https://aclanthology.org/2020.lrec-1.285/ (accessed 21.05.2024).
23. Kirillovich A., Nevzorova O. Ontological Analysis of the Wikipedia Category System. In: Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) KEOD. Seville, Spain: SciTePress; 2018. p. 358-366. https://doi.org/10.5220/0006961803580366
24. Suchanek F.M., Alam M., Bonald T., Chen L., Paris P.-H., Soria J. YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomy. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '24). New York, NY, USA: Association for Computing Machinery; 2024. p. 131-140. https://doi.org/10.1145/3626772.3657876
25. Vrandečić D., Pintscher L., Krötzsch M. Wikidata: The Making Of. In: Companion Proceedings of the ACM Web Conference 2023 (WWW '23 Companion). New York, NY, USA: Association for Computing Machinery; 2023. p. 615-624. https://doi.org/10.1145/3543873.3585579

This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication policy of the journal is based on traditional ethical principles of the Russian scientific periodicals and is built in terms of ethical norms of editors and publishers work stated in Code of Conduct and Best Practice Guidelines for Journal Editors and Code of Conduct for Journal Publishers, developed by the Committee on Publication Ethics (COPE). In the course of publishing editorial board of the journal is led by international rules for copyright protection, statutory regulations of the Russian Federation as well as international standards of publishing.
Authors publishing articles in this journal agree to the following: They retain copyright and grant the journal right of first publication of the work, which is automatically licensed under the Creative Commons Attribution License (CC BY license). Users can use, reuse and build upon the material published in this journal provided that such uses are fully attributed.
