Abstract
In the decision making of sales activities, the means for greatly increasing the efficiency of sales activities are required by eliminating individuals' factors such as experience and intuition In order to solve this problem we are developing the business decision support system using a machine learning model. For that, it is necessary to learn the process of sales activities with high order acceptance probability, so the process discovery technology that extracts regularity from the decision making is essential.
In the process discovery method in conventional process mining the regularity and rules of business process are extracted from information on execution order of events contained in the event logs output from the systems How ever in the decision making of sales activities it is difficult to apply the conventional process discovery method because the rules are not known in advance and the input information is unstructured data such as business diaries.
In this paper we provid e the process discovery method using the activity estimation based on unstructured data and the process estimation for stochastic expression of regularity in an atypical process for the process discovery method of decision making in sales activities.
