Research of Analysis Methods of Characteristics Set for Data Reduction on Multiple-choice Questions

At present, the analysis of multiple choice questions mainly focuses on the analysis and deduction of independent options in the field of survey and analysis without considering their relationships more or less. This paper presents two feature set analysis methods based on data reduction of multi-selection questions. Firstly, one or more options of the multiple-choice questions is considered as a feature combination, on behalf of its corresponding multiple choice of all the information, and then feature combination set (i.e. feature set) is digitally encoded. Secondly, in order to solve the problem of " dimensional explosion” of feature set, two kinds of data statistic methods, cumulative ratio and clustering, are proposed. Finally, the investigation of a case study shows the method’s rationality and effectiveness. The study provides a technical support for in-depth analysis of multiple selection issues in various fields.