Concept of Relational Similarity Search

D 2022

Concept of Relational Similarity Search

MÍČ, Vladimír a Pavel ZEZULA

Základní údaje

Originální název

Concept of Relational Similarity Search

Autoři

MÍČ, Vladimír (203 Česká republika, domácí) a Pavel ZEZULA (203 Česká republika, garant, domácí)

Vydání

Cham, Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5 - October 7, 2022, Proceedings, od s. 89-103, 15 s. 2022

Nakladatel

Springer

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Švýcarsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Impakt faktor

Impact factor: 0.402 v roce 2005

Kód RIV

RIV/00216224:14330/22:00127336

Organizační jednotka

Fakulta informatiky

ISBN

978-3-031-17848-1

ISSN

DOI

http://dx.doi.org/10.1007/978-3-031-17849-8_8

UT WoS

000874756300008

Klíčová slova anglicky

Efficient similarity search;Relational similarity;Similarity comparisons;Effective similarity search

Štítky

best, core_B, DISA, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 22. 11. 2023 16:43, RNDr. Vladimír Míč, Ph.D.

Anotace

V originále

For decades, the success of the similarity search has been based on a detailed quantification of pairwise similarity of objects. Currently, the search features have become much more precise but also bulkier, and the similarity computations more time-consuming. While the k nearest neighbours (kNN) search dominates the real-life applications, we claim that it is principally free of a need for precise similarity quantifications. Based on the well-known fact that a selection of the most similar alternative out of several options is a much easier task than deciding the absolute similarity scores, we propose the search based on an epistemologically simpler concept of relational similarity. Having arbitrary objects q,o1,o2 from the search domain, the kNN search is solvable just by the ability to choose the more similar object to q out of o1,o2 – the decision can also contain a neutral option. We formalise such searching and discuss its advantages concerning similarity quantifications, namely its efficiency and robustness. We also propose a pioneering implementation of the relational similarity search for the Euclidean spaces and report its extreme filtering power in comparison with 3 contemporary techniques.

Návaznosti

EF16_019/0000822, projekt VaV

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

Citovat

MÍČ, Vladimír a Pavel ZEZULA. Concept of Relational Similarity Search. In Tomáš Skopal, Fabrizio Falchi, Jakub Lokoč, Maria Luisa Sapino, Ilaria Bartolini, Marco Patella. Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5 - October 7, 2022, Proceedings. Cham: Springer, 2022, s. 89-103. ISBN 978-3-031-17848-1. Dostupné z: https://dx.doi.org/10.1007/978-3-031-17849-8_8.

@inproceedings{2236342,
   author = {Míč, Vladimír and Zezula, Pavel},
   address = {Cham},
   booktitle = {Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5 - October 7, 2022, Proceedings},
   doi = {http://dx.doi.org/10.1007/978-3-031-17849-8_8},
   editor = {Tomáš Skopal, Fabrizio Falchi, Jakub Lokoč, Maria Luisa Sapino, Ilaria Bartolini, Marco Patella},
   keywords = {Efficient similarity search;Relational similarity;Similarity comparisons;Effective similarity search},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Cham},
   isbn = {978-3-031-17848-1},
   pages = {89-103},
   publisher = {Springer},
   title = {Concept of Relational Similarity Search},
   url = {https://link.springer.com/chapter/10.1007/978-3-031-17849-8_8},
   year = {2022}
}

TY  - JOUR
ID  - 2236342
AU  - Míč, Vladimír - Zezula, Pavel
PY  - 2022
TI  - Concept of Relational Similarity Search
PB  - Springer
CY  - Cham
SN  - 9783031178481
KW  - Efficient similarity search;Relational similarity;Similarity comparisons;Effective similarity search
UR  - https://link.springer.com/chapter/10.1007/978-3-031-17849-8_8
N2  - For decades, the success of the similarity search has been based on a detailed quantification of pairwise similarity of objects. Currently, the search features have become much more precise but also bulkier, and the similarity computations more time-consuming. While the k nearest neighbours (kNN) search dominates the real-life applications, we claim that it is principally free of a need for precise similarity quantifications. Based on the well-known fact that a selection of the most similar alternative out of several options is a much easier task than deciding the absolute similarity scores, we propose the search based on an epistemologically simpler concept of relational similarity. Having arbitrary objects q,o1,o2 from the search domain, the kNN search is solvable just by the ability to choose the more similar object to q out of o1,o2 – the decision can also contain a neutral option. We formalise such searching and discuss its advantages concerning similarity quantifications, namely its efficiency and robustness. We also propose a pioneering implementation of the relational similarity search for the Euclidean spaces and report its extreme filtering power in comparison with 3 contemporary techniques.
ER  -

MÍČ, Vladimír a Pavel ZEZULA. Concept of Relational Similarity Search. In Tomáš Skopal, Fabrizio Falchi, Jakub Lokoč, Maria Luisa Sapino, Ilaria Bartolini, Marco Patella. \textit{Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5 - October 7, 2022, Proceedings}. Cham: Springer, 2022, s.~89-103. ISBN~978-3-031-17848-1. Dostupné z: https://dx.doi.org/10.1007/978-3-031-17849-8\_{}8.

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