Djamel Mostefa’s scientific contributions

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Publications (1)


Fig. 1. Basic polarity histogram
Measuring the Polarity of Conversations between Chatbots and Humans: A Use Case in the Banking Sector
  • Conference Paper
  • Full-text available

September 2020

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113 Reads

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2 Citations

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Djamel Mostefa

This paper describes a study on opinion analysis applied to both human to chatbot conversations, but also to human to human conversations using data coming from the banking sector. A polarity classifier SVM model applied to conversations provides insights and visualisations of the satisfaction of users at a given time and its evolution. We conducted a study on the evolution of the opinion on the conversations started with the chatbot and then transferred to a human agent. This work illustrates how opinion analysis techniques can be applied to improve the user experience of the customers but also detect topics that generate frustrations with a chatbot or with human experts.

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Citations (1)


... Visualizing conversational flows as state machines is especially useful for conceiving contextual conversations in contrast to FAQ-oriented conversations. In FAQ-oriented chatbots, every intent is mapped to one and only action, that is, for a given intent the response is always the same [Noé-Bienvenu et al., 2020]. On the other hand, contextoriented chatbots can select a different action for the same intent based on the actions and intents that happened previously, that is, the context of the conversation [Galitsky, 2019]. ...

Reference:

A Modeling Strategy for the Verification of Context-Oriented Chatbot Conversational Flows via Model Checking
Measuring the Polarity of Conversations between Chatbots and Humans: A Use Case in the Banking Sector