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Ontology-Based Models of Chatbots for Populating Knowledge Graphs

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Knowledge Graphs and Semantic Web (KGSWC 2023)

Abstract

Knowledge graphs and graph databases are nowadays extensively used in various domains. However, manually creating knowledge graphs using existing ontology concepts presents significant challenges. On the other hand, chatbots are one of the most prominent technologies in the recent past. In this paper, we explore the idea of utilizing chatbots to facilitate the manual population of knowledge graphs. To implement these chatbots, we generate them based on other special knowledge graphs that serve as models of chatbots. These chatbot models are created using our modelling ontology (specially designed for this purpose) and ontologies from a specific domain. The proposed approach enables the manual population of knowledge graphs in a more convenient manner through the use of automatically generated conversational agents based on our chatbot models.

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Notes

  1. 1.

    https://github.com/ontosoft/logic-interface/blob/main/ontology/obop.owl.

  2. 2.

    http://purl.org/tio/ns.

  3. 3.

    https://flask.palletsprojects.com.

  4. 4.

    https://github.com/ontosoft/ontochatbot.

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Correspondence to Petko Rutesic .

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Rutesic, P., Pfisterer, D., Fischer, S., Paulheim, H. (2023). Ontology-Based Models of Chatbots for Populating Knowledge Graphs. In: Ortiz-Rodriguez, F., Villazón-Terrazas, B., Tiwari, S., Bobed, C. (eds) Knowledge Graphs and Semantic Web. KGSWC 2023. Lecture Notes in Computer Science, vol 14382. Springer, Cham. https://doi.org/10.1007/978-3-031-47745-4_17

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  • DOI: https://doi.org/10.1007/978-3-031-47745-4_17

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  • Online ISBN: 978-3-031-47745-4

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