Russian-English dataset and comparative analysis of algorithms for cross-language embeddingbased entity alignment

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Russian-English dataset and comparative analysis of algorithms for cross-language embeddingbased entity alignment. / Gnezdilova, V. A.; Apanovich, Z. V.

In: Journal of Physics: Conference Series, Vol. 2099, No. 1, 012023, 13.12.2021.

Research output: Contribution to journal › Conference article › peer-review

BibTeX

@article{eb19a7c35bb74105aebc6c3e0ae54a70,

title = "Russian-English dataset and comparative analysis of algorithms for cross-language embeddingbased entity alignment",

abstract = "The problem of data fusion from data bases and knowledge graphs in different languages is becoming increasingly important. The main step of such a fusion is the identification of equivalent entities in different knowledge graphs and merging their descriptions. This problem is known as the identity resolution, or entity alignment methods has emerged. They look for the so called {"}embeddings{"} of entities and establish the equivalence of entities by comparing their embeddings. This paper presents experiments with embedding-based entity alignment algorithms on a Russian-English dataset. The purpose of this work is to identify language-specific features of the entity alignment algorithms. Also, future directions of research are outlined.",

author = "Gnezdilova, {V. A.} and Apanovich, {Z. V.}",

note = "Publisher Copyright: {\textcopyright} 2021 Institute of Physics Publishing. All rights reserved.; International Conference on Marchuk Scientific Readings 2021, MSR 2021 ; Conference date: 04-10-2021 Through 08-10-2021",

year = "2021",

month = dec,

day = "13",

doi = "10.1088/1742-6596/2099/1/012023",

language = "English",

volume = "2099",

journal = "Journal of Physics: Conference Series",

issn = "1742-6588",

publisher = "IOP Publishing Ltd.",

number = "1",

}

RIS

TY - JOUR

T1 - Russian-English dataset and comparative analysis of algorithms for cross-language embeddingbased entity alignment

AU - Gnezdilova, V. A.

AU - Apanovich, Z. V.

PY - 2021/12/13

Y1 - 2021/12/13

N2 - The problem of data fusion from data bases and knowledge graphs in different languages is becoming increasingly important. The main step of such a fusion is the identification of equivalent entities in different knowledge graphs and merging their descriptions. This problem is known as the identity resolution, or entity alignment methods has emerged. They look for the so called "embeddings" of entities and establish the equivalence of entities by comparing their embeddings. This paper presents experiments with embedding-based entity alignment algorithms on a Russian-English dataset. The purpose of this work is to identify language-specific features of the entity alignment algorithms. Also, future directions of research are outlined.

AB - The problem of data fusion from data bases and knowledge graphs in different languages is becoming increasingly important. The main step of such a fusion is the identification of equivalent entities in different knowledge graphs and merging their descriptions. This problem is known as the identity resolution, or entity alignment methods has emerged. They look for the so called "embeddings" of entities and establish the equivalence of entities by comparing their embeddings. This paper presents experiments with embedding-based entity alignment algorithms on a Russian-English dataset. The purpose of this work is to identify language-specific features of the entity alignment algorithms. Also, future directions of research are outlined.

UR - http://www.scopus.com/inward/record.url?scp=85123687026&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/2099/1/012023

DO - 10.1088/1742-6596/2099/1/012023

M3 - Conference article

AN - SCOPUS:85123687026

VL - 2099

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012023

T2 - International Conference on Marchuk Scientific Readings 2021, MSR 2021

Y2 - 4 October 2021 through 8 October 2021

ER -

ID: 35378396