Conversational Agents for Recipe Recommendation

As technology improves, the use of conversational agents to help users solve information seeking tasks is becoming ever more prevalent. To date we know little about how people behave with such systems, particularly in diverse contexts and for different tasks, their specific needs or how best to support these. By employing a Wizard of Oz (WoZ) methodology and developing a conversational framework, in this work we study how participants (n=28) interact with such a system in an attempt to solve recipe recommendation tasks. Our results are mostly encouraging for the future development of conversational agents in this context, however, they also provide insights into the complexities of building such a system that could convincingly engage with users in productive, human-like conversations.