Методы и алгоритмы повышения выразительности связанных данных (обзор)

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Ольга Авенировна Невзорова

Аннотация

В обзорной статье рассмотрены методы и алгоритмы повышения выразительности связанных данных, подготовленных для публикации в Вебе. Представлены основные подходы к обогащению онтологий, описаны методы, на которых они базируются, а также приведен инструментарий, реализующий эти подходы и инструменты применения соответствующих методов.Основным этапом в общей схеме жизненного цикла данных в облаке открытых связанных данных является этап построения набора связанных RDF-триплетов. Для улучшения классификации данных и анализа их качества применяются различные методы повышения выразительности связанных данных. Основные идеи рассматриваемых методов связаны с обогащением существующих онтологий (расширением базовой схемы знаний) путем добавления или совершенствования терминологических аксиом. Методы обогащения опираются на методы, применяемые в различных областях, таких как представление знаний, машинное обучение, статистика, обработка текстов на естественном языке, анализ формальных понятий и теория игр.

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Как цитировать
Невзорова, О. А. (2020). Методы и алгоритмы повышения выразительности связанных данных (обзор). Электронные библиотеки, 23(4), 808-834. https://doi.org/10.26907/1562-5419-2020-23-4-808-834
Биография автора

Ольга Авенировна Невзорова

Доцент кафедры информационных систем Института вычислительной математики и информационных технологий Казанского федерального университета, к. т. н. Основные направления научных исследований: обработка естественного языка, искусственный интеллект.

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