Algorithm of Apriori-Based Rural Tourism Driving Factors and Its System Optimization

Abstract

Rural tourism, as a vital component of tourism, is critical to the development of rural economies, farmers’ income, rural civilization, new rural construction, and urban-rural interaction. Simultaneously, as the size and complexity of data sets grow larger, how to improve the efficiency of association rule algorithms for mining large data sets has become a hot topic in association rule mining. Rural tourism development that is cultural and creative not only contributes to rural revitalization, but also to the preservation and inheritance of rural culture. The Apriori algorithm is the most widely used and influential algorithm for mining Boolean association rules, and the majority of current algorithms are extensions of the Apriori algorithm. Demand, supply, marketing, and support forces of rural tourism, which are the core driving force of rural tourism development, are formed by the basic needs of each subsystem of rural tourism. One of the main methods is to promote the sustainable and healthy development of rural tourism in accordance with the nature, characteristics, and laws of rural tourism destination construction, in order to create a dynamic system for long-term development and establish a rural tourism development dynamic system. The study of rural tourism driving factors and their system optimization is proposed in this paper. The main tourism dynamic system is adopted by the association rule algorithm of Apriori, the driving factors of rural tourism development are analyzed in the paper, and the system optimization method is proposed, all based on the Apriori algorithm. In terms of support, the Apriori algorithm is 0.436 higher than the CD algorithm and 0.568 higher than the SVM algorithm, and the Apriori algorithm can greatly reduce database size and improve record reading speed. As a result, the findings of this paper can be used to improve the spatial layout of rural tourism and to develop urban-rural tourism.

The border tourism hotspots network based on travelogues

“…In a study focusing on inbound tourists to China, the algorithm was used to identify co-occurring preference attributes at scenic spots, and based on these attributes, market segmentation was conducted, offering profound insights into the tourism market [ 61 ]. And the Apriori algorithm demonstrates significant potential in uncovering relationships between tourism destinations and holds value in understanding and promoting the development of rural tourism, among other areas [ 62 ]. This method not only assists researchers in identifying key driving factors but also provides scientific decision-making support for the formulation and implementation of tourism policies.…”

Development Drivers of Rural Summer Health Tourism for the Urban Elderly: A Demand- and Supply-Based Framework

“…Li [54] argued that the drivers of rural tourism development have five sub-systems: supply, demand, decision, media, and support. Xiao [55] suggested that the core drivers of rural tourism development are demand, supply, marketing, and support forces. Wang et al [56] divided the tourism drivers for rural revitalization into endogenous and exogenous drivers.…”