  Searching for new information requires talking to the system. In this
research, an Open-domain Conversational information search system has been
developed. This system has been implemented using the TREC CAsT 2019 track,
which is one of the first attempts to build a framework in this area. According
to the user's previous questions, the system firstly completes the question
(using the first and the previous question in each turn) and then classifies it
(based on the question words). This system extracts the related answers
according to the rules of each question. In this research, a simple yet
effective method with high performance has been used, which on average,
extracts 20% more relevant results than the baseline.
