Autores
Gelbukh Alexander
Título Sentiment analysis and opinion mining: Keynote address
Tipo Congreso
Sub-tipo Memoria
Descripción 2017 6th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions), AIIT, Amity University Uttar Pradesh, Noida, India
Resumen Sentiment analysis and opinion mining are closely related tasks that recently have received great attention from both research community and industry. Opinion mining is aimed to turn a huge amount of user-contributed context in Internet, such as tweets, product reviews, and blogs into useful information, which allows the companies and the governmental bodies to improve their product and services, and, on the other hand, allows the consumers to make informed buying decisions. Sentiment analysis, apart from its use in opinion mining, finds other important applications in security, healthcare, and education, among others. In this paper, I briefly discuss the motivation behind these tasks and outline some techniques recently developed by our group, mainly based on specially tailored deep-learning architectures or other machine-learning methods
Observaciones IEEE Xplore Digital Library, https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8342396, DOI: 10.1109/ICRITO.2017.8342396, AIIT, Amity University Uttar Pradesh.
Lugar Uttar Peadesh
País India
No. de páginas 41-47
Vol. / Cap.
Inicio 2017-09-20
Fin 2017-09-22
ISBN/ISSN 9781509030125