Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published.

Supermetric search with the four-point property

Vadicamo L;Cardillo FA;Rabitti F
2016

Abstract

Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC -
dc.authority.orgunit Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI -
dc.authority.people Connor R it
dc.authority.people Vadicamo L it
dc.authority.people Cardillo FA it
dc.authority.people Rabitti F it
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dc.contributor.appartenenza Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
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dc.date.accessioned 2024/02/20 07:35:48 -
dc.date.available 2024/02/20 07:35:48 -
dc.date.issued 2016 -
dc.description.abstracteng Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published. -
dc.description.affiliations University of Strathclyde, Glasgow, UK; CNR-ISTI, Pisa, Italy; CNR-ILC, Pisa, Italy; CNR-ISTI, Pisa, Italy -
dc.description.allpeople Connor, R; Vadicamo, L; Cardillo, Fa; Rabitti, F -
dc.description.allpeopleoriginal Connor R.; Vadicamo L.; Cardillo F.A.; Rabitti F. -
dc.description.fulltext partially_open en
dc.description.numberofauthors 4 -
dc.identifier.doi 10.1007/978-3-319-46759-7_4 -
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dc.identifier.uri https://hdl.handle.net/20.500.14243/313938 -
dc.identifier.url https://link.springer.com/chapter/10.1007%2F978-3-319-46759-7_4 -
dc.language.iso eng -
dc.miur.last.status.update 2024-09-24T14:18:16Z *
dc.relation.alleditors Amsaleg L., Houle M., Schubert E. -
dc.relation.conferencedate 24-26 October 2016 -
dc.relation.conferencename Similarity Search and Applications. 9th International Conference -
dc.relation.conferenceplace Tokyo, Japan -
dc.relation.firstpage 51 -
dc.relation.ispartofbook Similarity Search and Applications. SISAP 2016 -
dc.relation.lastpage 64 -
dc.subject.keywords Similarity search -
dc.subject.keywords Metric Space -
dc.subject.keywords Supermetric Space -
dc.subject.keywords Metric Indexing -
dc.subject.keywords Four-point property -
dc.subject.keywords Hilbert Embedding -
dc.subject.keywords H.3.3 INFORMATION STORAGE AND RETRIEVAL. Information Search and Retrieval -
dc.subject.singlekeyword Similarity search *
dc.subject.singlekeyword Metric Space *
dc.subject.singlekeyword Supermetric Space *
dc.subject.singlekeyword Metric Indexing *
dc.subject.singlekeyword Four-point property *
dc.subject.singlekeyword Hilbert Embedding *
dc.subject.singlekeyword H.3.3 INFORMATION STORAGE AND RETRIEVAL. Information Search and Retrieval *
dc.title Supermetric search with the four-point property en
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isi.contributor.affiliation Consiglio Nazionale delle Ricerche (CNR) -
isi.contributor.country Scotland -
isi.contributor.country Italy -
isi.contributor.country Italy -
isi.contributor.country Italy -
isi.contributor.name Richard -
isi.contributor.name Lucia -
isi.contributor.name Franco Alberto -
isi.contributor.name Fausto -
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isi.contributor.subaffiliation Dept Comp & Informat Sci -
isi.contributor.subaffiliation Inst Informat Sci & Technol ISTI -
isi.contributor.subaffiliation Inst Computat Linguist ILC -
isi.contributor.subaffiliation Inst Informat Sci & Technol ISTI -
isi.contributor.surname Connor -
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isi.description.abstracteng Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published. *
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scopus.description.abstracteng Metric indexing research is concerned with the efficient evaluation of queries in metric spaces. In general, a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query can be efficiently found. Most such mechanisms rely upon the triangle inequality property of the metric governing the space. The triangle inequality property is equivalent to a finite embedding property, which states that any three points of the space can be isometrically embedded in two-dimensional Euclidean space. In this paper, we examine a class of semimetric space which is finitely 4-embeddable in three-dimensional Euclidean space. In mathematics this property has been extensively studied and is generally known as the four-point property. All spaces with the four-point property are metric spaces, but they also have some stronger geometric guarantees. We coin the term supermetric space as, in terms of metric search, they are significantly more tractable. We show some stronger geometric guarantees deriving from the four-point property which can be used in indexing to great effect, and show results for two of the SISAP benchmark searches that are substantially better than any previously published. *
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