The article describes the prerequisites for creating an electronic notification system for students in an educational institution. A use case diagram is provided that describes interaction with the system from the point of view of the user-employee of the educational department and the user-student. A diagram of the physical database model is presented and a description of the purpose of the tables is given. The system uses two types of client applications: an administrative client for organizing the work of educational department employees and a Telegram bot for working on the students’ side. A scheme for working with user data when processing chatbot commands is defined in the IDEF0 notation. The choice of the interlocutor program as a communication tool was made based on the popularity of this technology. The administrative client is implemented in C# using Windows Forms technology, the chatbot is implemented in Python using the “schedule” time planning library, “time” working with time and “threading” multi-threading support.

Keywords: chat bot, Telegram bot, messenger, message, mobile device, information system, database, computer program, application

The relevance of creating a chatbot for advising applicants, promoting the university brand and raising awareness about the university is considered. The basic principles of the chatbot functioning are determined. Modeling of the sequence of processes using IDEF0 and UML is performed. The article contains a description of the chatbot algorithm. Activity and state diagrams are used to visualize this algorithm. The graphical interpretation of the logic of the interaction of the system elements is performed at the IDEF3 documentation level. A physical model for storing the data necessary for consultation is presented; the purpose of the tables obtained is described. The issues of fuzzy search by keywords are considered. The article describes the error correction process using the n-gram distance metric and the Damerau-Levenshtein metric. The functioning of the chatbot in the consultation mode when searching for keywords with errors in the user's message is demonstrated.

Keywords: chatbot, dialog system, messenger, natural language processing, fuzzy search, Damerau-Levenstein distance, n-gram