The CAMEO Project: A Holistic View for Conversational Agents Discussion Paper

The interaction with information access systems through conversational interfaces is becoming increasingly popular. Among the systems that benefit the most from this kind of interaction between the user and the system, we mention Information Retrieval (IR) systems and Recommender Systems (RS). A conversational interface in such scenarios has multiple advantages: first, it allows users to refine their needs, either in terms of information in an IR system or of an item in a RS, through multiple interactions also based on the system’s reaction to the user’s prompt. Secondly, it allows elderly, children and visually impaired people to access these kinds of systems easily. Nevertheless, conversational systems come with a plethora of additional challenges that need to be addressed, including a more complex querying language and a challenging evaluation – for which we often lack also evaluation data. Finally, Conversational IR and RS are often intended as separate tasks, with separate models and systems. We argue that such tasks could benefit from an integrated model capable of seamlessly dealing with them and exploiting the joint knowledge to improve its effectiveness. CAMEO is a project that aims to deal with such challenges. In this extended abstract, we outline the current state of the works within the CAMEO project and detail some future directions that we wish to explore.