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A support vector machines method for tourist satisfaction degree evaluation

Conference Paper


Abstract


  • 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 ofTSD is established through the classified-SVM with the use of one-on-one strategy; and finally for illustration, an exam pie 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. © 2009 IEEE.

Publication Date


  • 2009

Citation


  • Li, W., Xu, S., & Meng, W. (2009). A support vector machines method for tourist satisfaction degree evaluation. In Proceedings of the 2009 6th International Conference on Service Systems and Service Management, ICSSSM '09 (pp. 883-887). doi:10.1109/ICSSSM.2009.5175007

Scopus Eid


  • 2-s2.0-71049133433

Web Of Science Accession Number


Start Page


  • 883

End Page


  • 887

Abstract


  • 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 ofTSD is established through the classified-SVM with the use of one-on-one strategy; and finally for illustration, an exam pie 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. © 2009 IEEE.

Publication Date


  • 2009

Citation


  • Li, W., Xu, S., & Meng, W. (2009). A support vector machines method for tourist satisfaction degree evaluation. In Proceedings of the 2009 6th International Conference on Service Systems and Service Management, ICSSSM '09 (pp. 883-887). doi:10.1109/ICSSSM.2009.5175007

Scopus Eid


  • 2-s2.0-71049133433

Web Of Science Accession Number


Start Page


  • 883

End Page


  • 887