  Multi-party Conversational Systems are systems with natural language
interaction between one or more people or systems. From the moment that an
utterance is sent to a group, to the moment that it is replied in the group by
a member, several activities must be done by the system: utterance
understanding, information search, reasoning, among others. In this paper we
present the challenges of designing and building multi-party conversational
systems, the state of the art, our proposed hybrid architecture using both
rules and machine learning and some insights after implementing and evaluating
one on the finance domain.
