Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining

Whether the characteristics of rural tourism changes or not provides the scale and basis for judging whether the rural tourism landscape has changed, but it cannot provide a judgment on the impact of rural tourism landscape changes. The impact is relative to the rural tourism landscape goal. The det...

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Autor principal:	Qun Jiang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/e5de92a0270f411eb3c0de6518220684
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id	oai:doaj.org-article:e5de92a0270f411eb3c0de6518220684
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spelling	oai:doaj.org-article:e5de92a0270f411eb3c0de65182206842021-11-22T01:10:18ZAnalysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining1530-867710.1155/2021/8742950https://doaj.org/article/e5de92a0270f411eb3c0de65182206842021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8742950https://doaj.org/toc/1530-8677Whether the characteristics of rural tourism changes or not provides the scale and basis for judging whether the rural tourism landscape has changed, but it cannot provide a judgment on the impact of rural tourism landscape changes. The impact is relative to the rural tourism landscape goal. The determination of rural tourism landscape objectives provides a baseline for judging the direction and impact of rural tourism characteristics and provides a prerequisite for rural tourism landscape actions. The determination of the quality target of the rural tourism landscape is mainly determined by the internal process and external demand of the rural tourism landscape. Through in-depth research on the frequent pattern growth algorithm FP-Growth, the algorithm can find frequent item sets by not generating candidate item sets. The core of the algorithm is the frequent pattern tree FP-tree, which can efficiently compress the transaction database. Based on the advantages of FP-tree, this paper improves a FP_Apriori algorithm based on frequent pattern trees. This algorithm projects the entire transaction database onto the FP-tree, avoiding a lot of I/O overhead. At the same time, I propose a more directional and targeted search strategy for FP-tree, which reduces the running time of the algorithm and uses the principle of the Mapping_Apriori algorithm to prethin the frequent item sets. This article uses the text analysis method of network data to excavate the characteristics and internal structure of rural tourism demand. The rural tourism market has a wide range of needs and multiple levels, and traditional research methods such as questionnaires have limited sample size and sample structure. With the help of network data, text mining, and other statistical analysis methods, in-depth empirical research on the characteristics and spatial structure of rural tourism in a certain region can cover more research groups. The research confirms that the results of using text analysis and questionnaire analysis on the perception of destination image are relatively consistent. Therefore, the network text analysis method is an effective tool to study the demand structure of the rural tourism market.Qun JiangHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Qun Jiang Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
description	Whether the characteristics of rural tourism changes or not provides the scale and basis for judging whether the rural tourism landscape has changed, but it cannot provide a judgment on the impact of rural tourism landscape changes. The impact is relative to the rural tourism landscape goal. The determination of rural tourism landscape objectives provides a baseline for judging the direction and impact of rural tourism characteristics and provides a prerequisite for rural tourism landscape actions. The determination of the quality target of the rural tourism landscape is mainly determined by the internal process and external demand of the rural tourism landscape. Through in-depth research on the frequent pattern growth algorithm FP-Growth, the algorithm can find frequent item sets by not generating candidate item sets. The core of the algorithm is the frequent pattern tree FP-tree, which can efficiently compress the transaction database. Based on the advantages of FP-tree, this paper improves a FP_Apriori algorithm based on frequent pattern trees. This algorithm projects the entire transaction database onto the FP-tree, avoiding a lot of I/O overhead. At the same time, I propose a more directional and targeted search strategy for FP-tree, which reduces the running time of the algorithm and uses the principle of the Mapping_Apriori algorithm to prethin the frequent item sets. This article uses the text analysis method of network data to excavate the characteristics and internal structure of rural tourism demand. The rural tourism market has a wide range of needs and multiple levels, and traditional research methods such as questionnaires have limited sample size and sample structure. With the help of network data, text mining, and other statistical analysis methods, in-depth empirical research on the characteristics and spatial structure of rural tourism in a certain region can cover more research groups. The research confirms that the results of using text analysis and questionnaire analysis on the perception of destination image are relatively consistent. Therefore, the network text analysis method is an effective tool to study the demand structure of the rural tourism market.
format	article
author	Qun Jiang
author_facet	Qun Jiang
author_sort	Qun Jiang
title	Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
title_short	Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
title_full	Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
title_fullStr	Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
title_full_unstemmed	Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining
title_sort	analysis of rural tourism demand characteristics and experience differences based on association rule mining
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/e5de92a0270f411eb3c0de6518220684
work_keys_str_mv	AT qunjiang analysisofruraltourismdemandcharacteristicsandexperiencedifferencesbasedonassociationrulemining
_version_	1718418374795460608

Analysis of Rural Tourism Demand Characteristics and Experience Differences Based on Association Rule Mining

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