Аннотация
The paper is dedicated to applying a hybrid approach based on rules and machine learning for anaphora resolution in the Russian language. The model combines formal rules, the Extra Trees machine learning algorithm and the Balance Cascade algorithm for working with imbalanced learning sets. A number of features were obtained from the rules or were generated from other features; in addition, the syntactic context was taken into account. A neural network algorithm SyntaxNet was used to analyze the syntactic context.
Язык оригинала | английский |
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Название основной публикации | Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 |
Издатель | Institute of Electrical and Electronics Engineers Inc. |
Страницы | 36-40 |
Число страниц | 5 |
ISBN (электронное издание) | 9781538615935 |
DOI | |
Состояние | Опубликовано - 18 окт 2017 |
Событие | 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 - Novosibirsk, Akademgorodok, Российская Федерация Продолжительность: 12 апр 2017 → 13 апр 2017 |
Конференция
Конференция | 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 |
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Страна | Российская Федерация |
Город | Novosibirsk, Akademgorodok |
Период | 12.04.2017 → 13.04.2017 |