Semantic Search and Filtering with AI Agents
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43976495" target="_blank" >RIV/49777513:23520/25:43976495 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-031-88720-8_4" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-88720-8_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-88720-8_4" target="_blank" >10.1007/978-3-031-88720-8_4</a>
Alternative languages
Result language
angličtina
Original language name
Semantic Search and Filtering with AI Agents
Original language description
The rapid advancement of pre-trained large language models (LLMs) has enabled the creation of innovative applications, especially in natural language processing. This work employs LLMs alongside our in-house technologies to develop an intuitive database search engine that processes natural language queries. The system uses a network of AI agents, including prompted LLMs and single-purpose neural classifiers, to categorize user queries into conditions for filtering individual data sources or direct matches to database entries. Enhanced with a Retrieval-Augmented Generation (RAG) approach, the application allows users to search large databases conversationally through a voice-enabled web-based interface. Currently, in the demo stage, this project shows full pipeline functionality and has been tested with approximately 150 h of transcribed speech data. Initial findings confirm the overall concept of the application.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/EH23_021%2F0008436" target="_blank" >EH23_021/0008436: RandD of technologies for advanced digitization in the Pilsen metropolitan area (DigiTech)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Information Retrieval. Lecture Notes in Computer Science
ISBN
978-3-031-88719-2
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
5
Pages from-to
19-23
Publisher name
Springer
Place of publication
Cham
Event location
Lucca, Italy
Event date
Apr 6, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—