Uživatelské dotazování do dat pomocí chatbotů s umělou inteligencí
| Název práce v češtině: | Uživatelské dotazování do dat pomocí chatbotů s umělou inteligencí |
|---|---|
| Název v anglickém jazyce: | User Data Querying with AI-Powered Chatbots |
| Akademický rok vypsání: | 2024/2025 |
| Typ práce: | diplomová práce |
| Jazyk práce: | |
| Ústav: | Katedra softwarového inženýrství (32-KSI) |
| Vedoucí / školitel: | doc. Mgr. Martin Nečaský, Ph.D. |
| Řešitel: |
| Zásady pro vypracování |
| Imagine you're working at your university's data center, where there are countless databases containing tons of valuable information. These databases aren't just used for the school's own systems, but they're also used to generate reports, analyze data, and manage information in general. Basically, the entire school depends on being able to find answers to questions hidden in the data as quickly as possible. But there's a problem - there are only a few employees who really understand both the organization and the databases, and they're the only ones who can translate management's questions into database queries. This creates a bottleneck, where the people who have questions far outnumber the employees who can help them.
The goal of this project is to create a chatbot that anyone in the organization can use to ask questions. The chatbot will refine the query through conversation and eventually translate it into an evaluable database query. This means that instead of relying on a few knowledgeable employees, anyone can get the information they need quickly and easily. To make this possible, we'll use Large Language Models (LLMs). But we won't stop there - we'll refine the chatbot's knowledge with a conceptual data model of the organization and technical data artifacts generated from it in Dataspecer. |
| Seznam odborné literatury |
| [1] https://dataspecer.com/
[2] https://github.com/microsoft/DeepSpeed/tree/master/blogs%2Fdeepspeed-chat TBA |
| Předběžná náplň práce |
| Our research lab focuses on semantic data modeling to enhance efficiency and consistency in software and data engineering tasks. Utilizing our flagship tool, Dataspecer (https://dataspecer.com/), we automate various processes and promote seamless interoperability between systems. Through a range of student research projects, we explore innovative approaches to tackle complex challenges in developing software systems.
By joining this research project, you'll play an important role in transforming how your university's data center operates, making valuable information more accessible to everyone. You'll have the opportunity to work with cutting-edge Large Language Models and contribute to the development of a chatbot that streamlines database querying. This experience will not only enhance your technical skills but also enable you to make a tangible impact on the way data-driven insights are obtained within the organization. Don't miss this chance to be part of an important project that combines advanced technology and practical problem-solving. |