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Труды Института системного программирования РАН

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Сравнительный анализ нейронных сетей в задаче классификации побочных эффектов на уровне сущностей в англоязычных текстах

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Аннотация

В данной работе представлено экспериментальное исследование эффективности ряда моделей нейронных сетей для задачи классификации побочных эффектов на уровне сущностей. Задача анализа тональности на уровне аспектных терминов, в которых необходимо определить мнение по отношению к конкретному аспекту, активно исследуется в течении последнего десятилетия. Для решения данной задачи в прошедшие годы было предложено несколько архитектур нейронных сетей. Несмотря на то, что модели, основанные на этих архитектурах, имеют много общего, есть некоторые компоненты, которые отличают их друг от друга. В данной статье была исследована применимость разработанных для аспектно ориентированного анализа тональности нейросетевых моделей для классификации побочных эффектов. Для оценки эффективности данных методов были проведены обширные эксперименты на различных англоязычных текстах биомедицинской тематики, включающих в себя записи клинических карточек, научную литературу и данные из социальных сетей. Также мы сравнили предлагаемую модель с одной из наилучших на данный момент моделей, основанной на методе опорных векторов и большом наборе признаков.

Об авторах

И. С. Алимова
Казанский (Приволжский) федеральный университет
Россия


Е. В. Тутубалина
Казанский (Приволжский) федеральный университет
Россия


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Для цитирования:


Алимова И.С., Тутубалина Е.В. Сравнительный анализ нейронных сетей в задаче классификации побочных эффектов на уровне сущностей в англоязычных текстах. Труды Института системного программирования РАН. 2018;30(5):177-196.

For citation:


Alimova I.S., Tutubalina E.V. Entity-level classification of adverse drug reactions: a comparison of neural network models. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2018;30(5):177-196. (In Russ.)

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