Electrotechnical and Computer Engineering
Vol. 39 No. 09 (2024): Proceedings of Faculty of Technical Sciences
SOFTWARE SYSTEM FOR SEMANTIC TEXT SEARCH USING VECTOR DATABASE TECHNOLOGY
Abstract
This paper proposes an alternative approach to text search using vector databases and pretrained artificial intelligence models. The paper deals with the process of creating a vector representation of textual data, indexing them into different vector databases and the procedure of searching for similarities with user queries.
References
1. S. J. Russel i P. Norvig, u Artificial intelligence: a modern approach, New Jersey, Pearson Education, 2010, pp. 1-29.
2. J. R, „kaggle.com,“ [Na mreži]. Available: https://www.kaggle.com/datasets/jrobischon/wikipedia-movie-plots.
3. pinecone.io, „https://www.pinecone.io/,“ pinecone.io. [Na mreži].
4. „weaviate.io,“ Weaviate, [Na mreži]. Available: https://weaviate.io/developers/weaviate. [Poslednji pristup 16 February 2024].
5. „qdrant.tech,“ Qdrant, [Na mreži]. Available: https://qdrant.tech/documentation/. [Poslednji pristup 16 February 2024].
6. T. Wolf, L. Debut, V. Sanh, J. Chaumond, C. Delangue i A. Moi, „HuggingFace's Transformers: State-of-the-art Natural Language Processing,“ Hugging Face, Brooklyn, 2020.