A Framework for Building Adaptive Intelligent Virtual Assistants

Luc Lamontagne, Fran├žois Laviolette, Richard Khoury, and Alexandre Bergeron-Guyard

Keywords

Intelligent virtual assistant, Question answering systems, Information extraction, Topic modeling, Machine learning, Natural language processing

Abstract

This paper describes a framework to support the construction of intelligent virtual assistants (IVAs). An IVA agent is a software assistant capable of interacting with a user to support sense-making tasks, to determine information needs, to provide relevant information and to improve its performance based on user feedbacks. Currently, there is no integrated software environment available to develop such agents. We are exploring how we can integrate machine learning and natural language processing technologies, available as open source software, to support the construction of intelligent virtual assistants. The framework relies on a combination of question answering (Q/A), information extraction (IE) and user modeling components. In this paper, we present an overview of the work that is being conducted to build a prototype of the framework.

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