Research On User Experience Acquisition Method Supporting User Intention Change Recognition

With the advance of information technology and the development of the Internet, the service evolution is developing on the basis of service computing and software evolution research. Service evolution is the evolution of the system based on the user’s intention to provide the required services in order to meet the changing needs of users. User’s intention is the ideas and plans of the users to complete the work, the intention may be speculated through observation and analysis of user behavior and user behavior can be obtained through the context-aware environment. The user’s experience is the user behavior pattern that is obtained through the long-term observation and analysis of the environment and user behavior, which provides important priori knowledge for identifying the user’s intention change and obtaining the user’s needs. Our research team studies the service evolution and identification of the user’s intention change based on the situational theory and the Smart Meeting Room System, the system evolves according to the user’s intention change to meet the changing user’s needs. In order to support the identification of user’s intention change, this thesis studies the acquisition method of user’s experience in the SMR system.For the issue of user experience acquisition method in the SMR system, this thesis gives the description method of user experience, and proposes the acquisition method of the user’s experience based on the environmental context information. First of all, for the problem of how to generate the user’s desire, the reasoning user’s desire method based on Bayesian network is studied. In this method, using the desire reasoning Bayesian networks that is constitute of event nodes, action nodes and desire nodes infers the user’s desire and the probability of desire and determines the user’s desire according to the changes in the environment, and a desire inference algorithm is proposed based on the message spread inference algorithm. Secondly, for the problem of how to generate the two probability matrixes which represent the user experience, studies the user experience acquisition method basea association rule mining and the problem update of user experience. The two probability matrixes are the desire transfer probability matrix and the action-desire relationship matr The desire transfer probability matrix indicates the transfer relationship between desires and responses the changing needs of users. The action-desire relationship matrix representes the relationship between the user’s actions and desire. Finally, this thesis gives an analysis instance of the user experience acquisition process based on SMR system, and verifies the effectiveness of the method of generating desire based on the Bayesian network inference and the method of generating the user experience based on association rule mining.