A support vector machines method for tourist satisfaction degree evaluation

摘要

In order to solve the problem of tourist satisfaction degree (TSD is referred to as tourist satisfaction degree) evaluation, a new method based on support vector machine (SVM is referred to as the support vector machine) is used in this paper. First of all, according to the principles of designing the tourist satisfaction index system, a more comprehensive index system is built up; then the factor set which is regard as SVM training set can be quantified by indicators; thus the evaluation model of TSD is established through the classified-SVM with the use of one-on-one strategy; and finally for illustration, an example is utilized to show the feasibility of the SVM model in solving TSD problem with small sample data and high accuracy rate. The TSD model based on SVM can effectively solve the conflicts of multiple attributes in evaluation and provide a new research thought and method for evaluating satisfaction degree in other fields.