  Conversational search is a relatively young area of research that aims at
automating an information-seeking dialogue. In this paper we help to position
it with respect to other research areas within conversational Artificial
Intelligence (AI) by analysing the structural properties of an
information-seeking dialogue. To this end, we perform a large-scale dialogue
analysis of more than 150K transcripts from 16 publicly available dialogue
datasets. These datasets were collected to inform different dialogue-based
tasks including conversational search. We extract different patterns of mixed
initiative from these dialogue transcripts and use them to compare dialogues of
different types. Moreover, we contrast the patterns found in
information-seeking dialogues that are being used for research purposes with
the patterns found in virtual reference interviews that were conducted by
professional librarians. The insights we provide (1) establish close relations
between conversational search and other conversational AI tasks; and (2)
uncover limitations of existing conversational datasets to inform future data
collection tasks.
