1. A method of predicting user's position, comprising: creating, by a server, information on a plurality of location clusters by processing a plurality of position data for a user with a probability based clustering algorithm; receiving, by a server, a current position data of the user and determining a first location cluster to which the current data is mapped among the plurality of location clusters; and creating, by a server, second information related to a probability that the user moves from the first location cluster to a second location cluster among the plurality of location clusters, wherein the position data is a data tuple including latitude, longitude, and time, for all the plurality of location clusters, the information includes a determined representative position value of each of the location clusters, the information on the plurality of location clusters is information given in a type of a Markov-chain, each of the plurality of location clusters corresponds to a state of the Markov chain, and a probability that the user moves from the first location cluster to the second location cluster represents a probability that a first state of the Markov chain, which corresponds to the first location cluster, is transitioned to a second state of the Markov chain, which corresponds to the second location cluster.