Pavel Zezula and Team of Scientists Receive Award for Long-Term Contribution to the Scientific Community
The significant Taste of Time award at the SEBD 2024 conference for long-term contribution to the scientific community was given to work Indexing Metric Spaces with M-Tree from 1997 by Professor Pavel Zezula of FI MU and other scientists – F. Rabitti, P. Ciaccia, M. Patella.
The "Taste of Time" award is given to projects that remain important, respected, and influential in their field even after many years. This exceptional achievement confirms the long-term relevance and impact of research that shapes contemporary scientific and technical knowledge.
The paper "Indexing Metric Spaces with M-Tree" introduced a revolutionary method for indexing metric spaces, which has become crucial for developing similarity search. This search type is now essential for working with digital data and has found widespread application in areas such as image, sound, and genomic data analysis.
An extended version of this paper was published at the prestigious VLDB (Very Large Data Bases) conference. It has garnered more than 2600 citations, confirming its significant impact on the scientific community.
Another significant milestone of this work on M-Tree is that it laid the foundation for the series of international SISAP (Similarity Search and Applications) conferences held regularly and achieved "CORE Rank B" status. The 17th edition will occur this year in Providence, Rhode Island, USA.
In 2006, the book "Similarity Search: the Metric Space Approach" was published by Springer, further developing the ideas from the original article and serving as a critical resource for teaching and research in this field.
Interestingly, FI MU regularly offers a course dedicated to similarity search, whose teaching materials are also in demand at foreign universities.
The development of vector databases currently amplifies the importance of similarity search. These databases use neural networks for vector extraction, and similarity search structures like M-Tree ensure efficient and fast searches in these complex data sets.
Congratulations on this international success. This significant award confirms the long-term contribution of this work in information technology.
More information about the award and the SEBD conference can be found here, and the awarded paper can be read here.
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