基于模糊逻辑和神经网络的酒店管理文本挖掘方法

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-06-07 DOI:10.3233/JIFS-219095
Peilin Chen, Qun Chen
{"title":"基于模糊逻辑和神经网络的酒店管理文本挖掘方法","authors":"Peilin Chen, Qun Chen","doi":"10.3233/JIFS-219095","DOIUrl":null,"url":null,"abstract":"With the rapid economic development, people cannot do without hotels in daily life and travel. The number of hotels is increasing rapidly, and the competitiveness between hotels is gradually increasing. A reasonable and sound hotel management system has become the key to the survival and development of an enterprise. The operation and operation of a hotel generates a large amount of information and data every day. Data text mining is an important method in current information processing technology. The purpose of this article is to explore the specific application effects of text mining methods based on fuzzy logic and neural networks in hotel management. Through the design of a hotel management system based on fuzzy logic and neural network, text mining database design is carried out according to hotel management needs, and the application effect of the hotel management system is evaluated. The evaluation indicators include customer satisfaction, operating costs, management efficiency, and hotel income. The results of the study show that the hotel management system based on fuzzy logic and neural network text mining can increase customer satisfaction by 37.4%, the hotel’s comprehensive management efficiency by 28.6%, and the hotel’s revenue level by 23.5%. At the same time, through the text mining of the key information generated in the hotel operation and management, the weak links in the management system can be strengthened and the hotel operation cost can be saved. Therefore, it is feasible to apply the text mining method based on fuzzy logic and neural network to hotel management.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":"33 1","pages":"1-10"},"PeriodicalIF":1.5000,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method of text mining based on fuzzy logic and neural network in hotel management\",\"authors\":\"Peilin Chen, Qun Chen\",\"doi\":\"10.3233/JIFS-219095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid economic development, people cannot do without hotels in daily life and travel. The number of hotels is increasing rapidly, and the competitiveness between hotels is gradually increasing. A reasonable and sound hotel management system has become the key to the survival and development of an enterprise. The operation and operation of a hotel generates a large amount of information and data every day. Data text mining is an important method in current information processing technology. The purpose of this article is to explore the specific application effects of text mining methods based on fuzzy logic and neural networks in hotel management. Through the design of a hotel management system based on fuzzy logic and neural network, text mining database design is carried out according to hotel management needs, and the application effect of the hotel management system is evaluated. The evaluation indicators include customer satisfaction, operating costs, management efficiency, and hotel income. The results of the study show that the hotel management system based on fuzzy logic and neural network text mining can increase customer satisfaction by 37.4%, the hotel’s comprehensive management efficiency by 28.6%, and the hotel’s revenue level by 23.5%. At the same time, through the text mining of the key information generated in the hotel operation and management, the weak links in the management system can be strengthened and the hotel operation cost can be saved. Therefore, it is feasible to apply the text mining method based on fuzzy logic and neural network to hotel management.\",\"PeriodicalId\":44705,\"journal\":{\"name\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"volume\":\"33 1\",\"pages\":\"1-10\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/JIFS-219095\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-219095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0

摘要

随着经济的快速发展,人们在日常生活和旅游中都离不开酒店。酒店数量迅速增加,酒店之间的竞争力也逐渐增强。合理健全的酒店管理制度已成为企业生存和发展的关键。酒店的经营和运营每天都会产生大量的信息和数据。数据文本挖掘是当前信息处理技术中的一种重要方法。本文的目的是探讨基于模糊逻辑和神经网络的文本挖掘方法在酒店管理中的具体应用效果。通过设计一个基于模糊逻辑和神经网络的酒店管理系统,根据酒店管理需求进行文本挖掘数据库设计,并对酒店管理系统的应用效果进行评价。评价指标包括顾客满意度、经营成本、管理效率和酒店收入。研究结果表明,基于模糊逻辑和神经网络文本挖掘的酒店管理系统可使客户满意度提高37.4%,酒店综合管理效率提高28.6%,酒店收入水平提高23.5%。同时,通过对酒店经营管理中产生的关键信息进行文本挖掘,加强管理系统中的薄弱环节,节约酒店经营成本。因此,将基于模糊逻辑和神经网络的文本挖掘方法应用于酒店管理是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Method of text mining based on fuzzy logic and neural network in hotel management
With the rapid economic development, people cannot do without hotels in daily life and travel. The number of hotels is increasing rapidly, and the competitiveness between hotels is gradually increasing. A reasonable and sound hotel management system has become the key to the survival and development of an enterprise. The operation and operation of a hotel generates a large amount of information and data every day. Data text mining is an important method in current information processing technology. The purpose of this article is to explore the specific application effects of text mining methods based on fuzzy logic and neural networks in hotel management. Through the design of a hotel management system based on fuzzy logic and neural network, text mining database design is carried out according to hotel management needs, and the application effect of the hotel management system is evaluated. The evaluation indicators include customer satisfaction, operating costs, management efficiency, and hotel income. The results of the study show that the hotel management system based on fuzzy logic and neural network text mining can increase customer satisfaction by 37.4%, the hotel’s comprehensive management efficiency by 28.6%, and the hotel’s revenue level by 23.5%. At the same time, through the text mining of the key information generated in the hotel operation and management, the weak links in the management system can be strengthened and the hotel operation cost can be saved. Therefore, it is feasible to apply the text mining method based on fuzzy logic and neural network to hotel management.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
期刊最新文献
Four Types of Generalized Fuzzy Continuous Mappings Analytic Review of Healthcare Software by Using Quantum Computing Security Techniques Hybrid Metaheuristic Technique for Optimization of Virtual Machine Placement in Cloud Complex Fuzzy Rough Aggregation Operators and their Applications in EDAS for Multi-Criteria Group Decision-Making Efficient Multi-Task CNN for Face and Facial Expression Recognition Using Residual and Dense Architectures for Application in Monitoring Online Learning
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1