PURPOSE: A conversation classification method is provided to classify conversation intention without a user or a manage by using an LUL(Nonparametric Unsupervised Learning) method. CONSTITUTION: An HMM(Hidden Markov Model) hiding the articulation intention of inputted articulation is applied to a generated model. An entity name recognition model recognizing a non-entity name word and an entity name from a construction word of the inputted articulation is applied to a recognition model. A lable is applied to the inputted articulation by defining the lable for the articulation intention based on a word separated by the entity name recognition model. The HMM is a Bayesian HMM or an HDP(Hierarchical Dirichlet Process) HMM, and the state entity is set as an infinite quantity.
