Informace o projektu
Naučené indexy pro podobností hledání
- Kód projektu
- GF23-07040K
- Období řešení
- 7/2023 - 6/2026
- Investor / Programový rámec / typ projektu
-
Grantová agentura ČR
- LA granty
- Lead agentura
- Fakulta / Pracoviště MU
- Fakulta informatiky
- Spolupracující organizace
-
Christian-Albrechts-Universtät zu Kiel
- Odpovědná osoba prof. Dr. Peer Kröger
When faced with the task of storing and retrieving complex, unstructured or high-dimensional data (e.g., multimedia data), metric spaces are often employed as an underlying mathematical concept for their organization. Consequently, the only measure that can be used to arrange the data is a pairwise similarity between data objects. Similarity searching refers to a range of methods used to manage data enabling efficient search in such spaces. The main paradigm of similarity searching has remained mostly unchanged for decades -- data objects are organized into a hierarchical structure according to their mutual distances, using representative pivots to reduce the number of distance computations needed to efficiently search the data.
We plan to investigate an alternative to this paradigm, using machine learning models to replace pivots, thus, posing similarity search as a classification problem. We will use both supervised and unsupervised approaches to implement our solutions. We will also address the questions of scalability and dynamicity, and verify the applications for metric data.
Cíle udržitelného rozvoje
Masarykova univerzita se hlásí k cílům udržitelného rozvoje OSN, jejichž záměrem je do roku 2030 zlepšit podmínky a kvalitu života na naší planetě.
Publikace
Počet publikací: 17
2024
-
3D-af-Surfer: Protein structural embeddings of AlphaFold DB
Rok: 2024, druh: Specializovaná databáze
-
3DZD: Protein structural embeddings of AlphaFold DB v4
Rok: 2024, druh: Specializovaná databáze
-
3DZD: Protein structural embeddings of ESM Atlas
Rok: 2024, druh: Specializovaná databáze
-
Advancing the PAM Algorithm to Semi-Supervised k-Medoids Clustering
17th International Conference on Similarity Search and Applications (SISAP), rok: 2024
-
AlphaFind
Rok: 2024
-
AlphaFind — discover structure similarity across the proteome in AlphaFold DB
Rok: 2024, druh: Konferenční abstrakty
-
AlphaFind — discover structure similarity across the proteome in AlphaFold DB
Rok: 2024, druh: Konferenční abstrakty
-
AlphaFind: Discover structure similarity across the entire known proteome
Rok: 2024
-
AlphaFind: Discover structure similarity across the entire known proteome – data and model
Rok: 2024, druh: Specializovaná databáze
-
AlphaFind: discover structure similarity across the proteome in AlphaFold DB
Nucleic acids research, rok: 2024, ročník: 52, vydání: July 5, DOI