An automatic procedure to create fuzzy ontologies from users’ opinions using sentiment analysis procedures and multi-granular fuzzy linguistic modelling methods

The high amount of information that users continually provides to the Internet is unorganized and difficult to interpret. Unluckily, there is no point in having high amounts of information that we cannot work with. Therefore, there is a need of methods that sort this information and stores it in a way that can be easily accessed and processed. In this paper, a novel method that uses sentiment analysis procedures in order to automatically create fuzzy ontologies from free texts provided by users in social networks is presented. Moreover, multi-granular fuzzy linguistic modelling methods are used in order to select the best representation mean to store the information in the fuzzy ontology. Thanks to the presented method, information is transformed and presented in an organized way making it possible to properly work with it. © 2018 Elsevier Inc.

Авторы
Morente-Molinera J.A.1 , Kou G.2 , Pang C.3 , Cabrerizo F.J.4 , Herrera-Viedma E. 4, 5
Журнал
Издательство
Elsevier Inc.
Язык
Английский
Страницы
222-238
Статус
Опубликовано
Том
476
Год
2019
Организации
  • 1 Department of Engineering, School of Engineering and Technology, Universidad Internacional de la Rioja (UNIR), Logroño, Spain
  • 2 School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China
  • 3 School of Business, Macau University of Science and Technology, Macau
  • 4 Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
  • 5 Peoples’ Friendship University of Russia (RUDN University), Moscow, Russian Federation
Ключевые слова
Fuzzy ontologies; Sentiment analysis; Social networks
Дата создания
04.02.2019
Дата изменения
04.02.2019
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/36074/
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