- Код статьи
- S30346444S0002338825040092-1
- DOI
- 10.7868/S3034644425040092
- Тип публикации
- Статья
- Статус публикации
- Опубликовано
- Авторы
- Том/ Выпуск
- Том / Номер выпуска 4
- Страницы
- 132-148
- Аннотация
- Рекомендательные системы находят все более широкое применение, охватывая множество сфер. Вместе с тем возрастает количество нестандартных случаев, связанных с необычными типами данных, на которых традиционные подходы не всегда эффективны. Например, при ограниченном количестве объектов более результативным решением становятся методы, основанные на обычных алгоритмах классификации. Предлагается способ повышения качества рекомендаций в рамках такого подхода за счет учета негативных взаимодействий пользователей с объектами. Интеграция этой информации позволяет более точно моделировать как предпочтения, так и избегаемые элементы. Представленный метод улучшает персонализацию рекомендаций даже в условиях высокой взаимосвязанности и ограниченности количества объектов.
- Ключевые слова
- рекомендательные системы отрицательные действия бустинг пользователи и объекты
- Дата публикации
- 05.05.2025
- Год выхода
- 2025
- Всего подписок
- 0
- Всего просмотров
- 19
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