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Обзор и экспериментальное сравнение методов кластеризации текстов

https://doi.org/10.15514/ISPRAS-2017-29(2)-6

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Аннотация

Кластеризация текстовых документов применяется во многих приложениях, таких как информационный поиск, исследовательский поиск, определение спама. Этой задаче посвящено множество научных работ, однако в настоящее время остается недостаточно изученным влияние специфики научных статей, в частности принадлежности документов одной предметной области или недоступности полных текстов, на эффективность кластеризации. В данной работе предлагаются обзор и экспериментальное сравнение методов кластеризации текстовых документов в приложении к научным статьям. Исследуются методы, основанные на мешке слов, извлечении терминологии, тематическом моделировании, а также векторном представлении слов (word embedding) и документов, полученном с помощью искусственных нейронных сетей (word2vec, paragraph2vec).

Об авторах

П. А. Пархоменко
Институт системного программирования РАН; Московский государственный университет имени М.В. Ломоносова
Россия


А. А. Григорьев
Институт системного программирования РАН; Национальный исследовательский университет «Высшая школа экономики»
Россия


Н. А. Астраханцев
Институт системного программирования РАН
Россия


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Для цитирования:


Пархоменко П.А., Григорьев А.А., Астраханцев Н.А. Обзор и экспериментальное сравнение методов кластеризации текстов. Труды Института системного программирования РАН. 2017;29(2):161-200. https://doi.org/10.15514/ISPRAS-2017-29(2)-6

For citation:


Parhomenko P.A., Grigorev A.A., Astrakhantsev N.A. A survey and an experimental comparison of methods for text clustering: application to scientific articles. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2017;29(2):161-200. (In Russ.) https://doi.org/10.15514/ISPRAS-2017-29(2)-6

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