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

V. A. Gnezdilova, Z. V. Apanovich

Результат исследования: Научные публикации в периодических изданияхстатья по материалам конференциирецензирование

Аннотация

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.

Язык оригиналаанглийский
Номер статьи012023
ЖурналJournal of Physics: Conference Series
Том2099
Номер выпуска1
DOI
СостояниеОпубликовано - 13 дек 2021
СобытиеInternational Conference on Marchuk Scientific Readings 2021, MSR 2021 - Novosibirsk, Virtual, Российская Федерация
Продолжительность: 4 окт 20218 окт 2021

Предметные области OECD FOS+WOS

  • 1.03 ФИЗИЧЕСКИЕ НАУКИ И АСТРОНОМИЯ

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