Quantitative Evaluation of Domestic Cultural and Tourism Integration Policies Based on PMC Index Modeling

Abstract

Abstract This paper constructs a text mining and quantitative evaluation model for cultural and tourism integration policies based on LDA and PMC index models. We find research samples of cultural and tourism integration policies through relevant websites and databases and use the LDA model to mine high-frequency words in the policies and make a high-frequency glossary. The quantitative evaluation index system of cultural and tourism policies is constructed according to the glossary and the definitions of policy evaluation by authoritative scholars, and then the scores of each policy are calculated based on the PMC formula, and the PCM surface diagram is drawn for quantitative evaluation. The results show that 57.14% of the 63 policies belong to the excellent level, and most of the policies have high scores in terms of policy timeliness, subject, tool, field, evaluation, and function, ranging from 0.5 to 0.8. Thirteen policies were poorly rated in terms of policy nature, with only 0.333-05, and there is much room for improvement. Based on the results of the study, an optimization concept focusing on optimizing the nature of policies is proposed to improve the problems existing in the current policy formulation of cultural tourism integration.