Concept of Relational Similarity Search

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00127336" target="_blank" >RIV/00216224:14330/22:00127336 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-031-17849-8_8" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-17849-8_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-17849-8_8" target="_blank" >10.1007/978-3-031-17849-8_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Concept of Relational Similarity Search

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Concept of Relational Similarity Search

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000822" target="_blank" >EF16_019/0000822: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Similarity Search and Applications: 15th International Conference, SISAP 2022, Bologna, Italy, October 5 - October 7, 2020, Proceedings

ISBN

9783031178481

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

15

Strana od-do

89-103

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Bologna, Itálie

Datum konání akce

1. 1. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000874756300008