  The use of natural language interfaces in the field of human-computer
interaction is undergoing intense study through dedicated scientific and
industrial research. The latest contributions in the field, including deep
learning approaches like recurrent neural networks, the potential of
context-aware strategies and user-centred design approaches, have brought back
the attention of the community to software-based dialogue systems, generally
known as conversational agents or chatbots. Nonetheless, and given the novelty
of the field, a generic, context-independent overview on the current state of
research of conversational agents covering all research perspectives involved
is missing. Motivated by this context, this paper reports a survey of the
current state of research of conversational agents through a systematic
literature review of secondary studies. The conducted research is designed to
develop an exhaustive perspective through a clear presentation of the
aggregated knowledge published by recent literature within a variety of
domains, research focuses and contexts. As a result, this research proposes a
holistic taxonomy of the different dimensions involved in the conversational
agents' field, which is expected to help researchers and to lay the groundwork
for future research in the field of natural language interfaces.
