1. An automated Wireless Local Area Network (WLAN) radio map construction method, comprising: generating a learning model based on Finite State Automata (FSA) in which divided areas of an indoor map are expressed by location states; and learning to arrange collected WLAN fingerprints in corresponding location states through machine learning based on the learning model, wherein the learning comprises: setting representative WLAN fingerprints for the location states; and arranging the collected WLAN fingerprints in the corresponding location states with reference to the representative WLAN fingerprints, and wherein the setting comprises: finding Access Points (APs) from the collected WLAN fingerprints, randomly arranging the found APs in the location states, and assigning the representative WLAN fingerprints to the location states with reference to an arraignment of the APs and a WLAN signal propagation model, wherein a number of APs included in an initial value of the learning model is variable, wherein the number of APs included in the initial value is dynamically determined by increasing the number of APs until a condition in which a location range determined by trilateration is not distributed and is determined to be a single range less than or equal to a predetermined size is satisfied, and wherein an order of the APs included in the initial value is determined with reference to Information Gain (IG).