[en] This paper introduces the personalization framework PERSEUS in order to investigate the impact of individuality in sentiment categorization by looking into the past. The existence of diversity between individuals and certain consistency in each individual is the cornerstone of the framework. We focus on relations between documents for user-sensitive predictions. Individual’s lexical choices act as indicators for individuality, thus we use a concept-based system which utilizes neural networks to embed concepts and associated topics in text. Furthermore, a recurrent neural network is used to memorize the history of user’s opinions, to discover user-topic dependence, and to detect implicit relations between users. PERSEUS also offers a solution for data sparsity. At the first stage, we show the benefit of inquiring a user-specified system. Improvements in performance experimented on a combined Twitter dataset are shown over generalized models. PERSEUS can be used in addition to such generalized systems to enhance the understanding of user’s opinions.
Disciplines :
Computer science
Author, co-author :
Guo, Siwen ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Höhn, Sviatlana; AI Minds > Vianden, Luxembourg
Xu, Feiyu; Lenovo > Beijing, China
Schommer, Christoph ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
External co-authors :
yes
Language :
English
Title :
PERSEUS: A Personalization Framework for Sentiment Categorization with Recurrent Neural Network
Publication date :
January 2018
Event name :
10th International Conference on Agents and Artificial Intelligence
Event place :
Funchal, Portugal
Event date :
from 16-01-2018 to 18-01-2018
Audience :
International
Main work title :
International Conference on Agents and Artificial Intelligence , Funchal 16-18 January 2018
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