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Automating Hierarchical Subject Index Construction for Scientific Documentsстатья
Информация о цитировании статьи получена из
Scopus
Дата последнего поиска статьи во внешних источниках: 1 февраля 2021 г.
- Авторы: Bolshakova E.I., Ivanov K.M.
- Сборник: The Eighteenth Russian Conference on Artificial Intelligence RCAI-2020
- Серия: Lecture Notes on Artificial Intelligence
- Том: 12412
- Год издания: 2020
- Место издания: Springer
- Первая страница: 1
- Последняя страница: 14
- DOI: 10.1007/978-3-030-59535-7_14
- Аннотация: Subject, or back-of-the-book index consists of significant terms with relevant page numbers of the text document, thus providing an easy access to its content. The paper describes methods developed for automating main stages of subject indexing for specialized texts: namely, term extraction, selection of the most important ones, detecting their reference pages, as well as recognizing semantic relations among selected index terms in order to structure them into hierarchy. The developed methods are intended for processing scientific documents in Russian and are based both on formal linguistics rules and unsupervised machine learning. Experimental evaluation of the methods have shown their sufficient quality to be built into computer subject indexing system.
- Добавил в систему: Большакова Елена Игоревна