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Hakim Lounis

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2 papers

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AAAI Conference 2020 Short Paper

Complex Emotional Intelligence Learning Using Deep Neural Networks (Student Abstract)

Belainine Billal
Fatiha Sadat
Hakim Lounis

Emotion recognition and mining tasks are often limited by the availability of manually annotated data. Several researchers have used emojis and speciﬁc hashtags as forms of training and supervision. This research paper proposes a new textual and social corpus, the corpus labeled using basic emotions following Plutchik’s theory. Thus, This paper propose a ﬁrst study for the representation and interpretation of complex emotional interactions, using deep neural networks.

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AAAI Conference 2020 Short Paper

Modelling a Conversational Agent with Complex Emotional Intelligence

Billal Belainine
Fatiha Sadat
Hakim Lounis

Chatbots or conversational agents have enjoyed great popularity in recent years. They surprisingly perform sensitive tasks in modern societies. However, despite the fact that they offer help, support, and fellowship, there is a task that is not yet mastered: dealing with complex emotions and simulating human sensations. This research aims to design an architecture for an emotional conversation agent for long-text conversations (multi-turns). This agent is intended to work in areas where the analysis of users feelings plays a leading role. This work refers to natural language understanding and response generation.

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