Generating Personalized Answers by Constructing a Question Situation.

This paper proposes a methodology to generate the personalized answer based on a question situation. To construct the question situation, personal learning characteristics should be obtained by principal component analysis and question type vector is used in the process of semantic analysis. After these analyses, the question situation is constructed based on a harmony network. The answer parameters, including answer depth and answer presentation pattern, are calculated by harmony function. According to these parameters, the personalized answer is matched by the adaptive neuro-fuzzy inference (ANFI). The system architecture of personalized answer generation is proposed in this paper and takes a learner's question to demonstrate. [ABSTRACT FROM AUTHOR]