Розробка підходу до формування фреймового словника для персоналізації освітнього чат-боту

The object of research is the process of functioning and using AI-based educational chatbots in the educational environment. The problem addressed in the research is the training of chatbots using dictionaries. The paper presents an approach to chatbot personalization through the use of a thematic dictionary and query adjustment with the help of prompts. A frame-based model of a dictionary has been developed, which can be added to a chatbot as a PDF document. The frames represent the subject domain as a hierarchically organized system. User prompts and the processing of frame structures are integrated with the chatbot through thematic representations. This ensures flexible query formulation, scalability of dictionary resources, and the possibility of further expansion of the subject domain without violating the integrity of the language model. Schemes for combining contextual projection of query interaction and dictionary search have been developed and substantiated. To implement prompts, an algorithm was designed based on the principle of a “marked bullet” selection of a term or expression. Chatbot personalization is achieved through the formation of a series of user-generated prompts. Based on the results of experiments on adapting ChatGPT to users’ educational needs, frame-based dictionaries were implemented and tested. For the sequential dictionary implementation scheme, at an accuracy level of 10⁻⁶, the total computational complexity is approximately 4.67, while increasing the accuracy requirement to 10⁻⁸ reduces this value to 3.287. The hierarchical scheme, based on the frame organization of the dictionary and the use of TemaView, demonstrates comparable or lower complexity values (10⁻⁶ = 6.69 and 10⁻⁸ = 4.69). The practical application lies in supporting the educational process through the use of personalized educational chatbots within learning systems.