[1]张旭辉,张 郴,李雅南,等.城市旅游餐饮体验的注意力机制模型建构——基于机器学习的网络文本深度挖掘[J].南京师大学报(自然科学版),2022,45(01):32-39.[doi:10.3969/j.issn.1001-4616.2022.01.006]
　Zhang Xuhui,Zhang Chen,Li Yanan,et al.Construction of Attention Mechanism Model of Urban Tourism Catering Experience:Deep Mining of Online Text Based on Machine Learning[J].Journal of Nanjing Normal University(Natural Science Edition),2022,45(01):32-39.[doi:10.3969/j.issn.1001-4616.2022.01.006]
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城市旅游餐饮体验的注意力机制模型建构——基于机器学习的网络文本深度挖掘()
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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第45卷
期数:
2022年01期
页码:
32-39
栏目:
·地理学·
出版日期:
2022-03-15

文章信息/Info

Title:
Construction of Attention Mechanism Model of Urban Tourism Catering Experience:Deep Mining of Online Text Based on Machine Learning
文章编号:
1001-4616(2022)01-0032-08
作者:
张旭辉1; 2; 张 郴1; 2; 李雅南1; 2; 徐梓榆1; 2; 黄震方1; 2
(1.南京师范大学地理科学学院,江苏 南京 210023)(2.江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023)
Author(s):
Zhang Xuhui1; 2; Zhang Chen1; 2; Li Yanan1; 2; Xu Ziyu1; 2; Huang Zhenfang1; 2
(1.School of Geography,Nanjing Normal University,Nanjing 210023,China)(2.Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)
关键词:
旅游餐饮体验; 注意力机制; 机器学习; 双因素理论; 网络文本
Keywords:
tourism catering experience; Attention mechanism; machine learning; two factor theory; online text
分类号:
F592.7
DOI:
10.3969/j.issn.1001-4616.2022.01.006
文献标志码:
A
摘要:
良好的旅游餐饮体验对提升城市旅游竞争力的意义不可小觑. 旅游餐饮文本记录了游客对旅游目的地餐饮店的产品和服务的真实体验,文本内容海量且受时空约束较小,颇具一定的分析价值. 本文将Attention机制(注意力机制)融合机器学习方法中的卷积神经网络模型,旨在对餐饮文本背后的深层语义关联进行深度挖掘,探寻影响游客积极餐饮体验的激励因素和消极餐饮体验的保健因素及其影响机制,这适用于旅游餐饮文本自身特质. 通过注意力机制模型建构,发现影响游客对南京餐饮体验评价的保健因素由价格、区位交通和服务组成,而激励因素则由口味、名气和文化环境组成. 另外,本文对注意力权重排序,优先解决权重较高因素,提升游客餐饮体验.
Abstract:
The significance of a good tourist catering experience in enhancing the competitiveness of urban tourism cannot be underestimated. The tourist catering text records the real experience of tourists to the products and services of the catering shops in the tourist destination. The text has a large amount of content and is less constrained by time and space,which has certain analytical value. This paper integrates Attention mechanism with the convolutional neural network model in the machine learning method,and aims to deeply explore the deep semantic associations behind the catering text,and explore the motivational factors that affect tourists’ positive catering experience and the healthcare factors of negative catering experience and their influencing mechanisms,which are applicable to the characteristics of tourist catering texts themselves. Through the construction of attention mechanism model,it is found that the healthcare factors that affect tourists’ uation of Nanjing’s catering experience are composed of price,location,transportation and services,while the motivational factors are composed of taste,fame and cultural environment. In addition,this paper sorts the value of attention weight,and prioritizes the resolution of higher-weight factors to improve the catering experience of tourists.

参考文献/References:

[1] 张海平,周星星,汤国安,等. 基于GIS场模型的城市餐饮服务热点探测及空间格局分析[J]. 地理研究,2020,39(2):354-369.
[2]秦萧,甄峰,朱寿佳,等. 基于网络口碑度的南京城区餐饮业空间分布格局研究——以大众点评网为例[J]. 地理科学,2014,34(7):810-817.
[3]李建州,白翠玲. 三类餐馆顾客体验实证研究[J]. 旅游学刊,2008,23(1):36-40.
[4]吴丽云,陈方英. 基于网络评论内容分析的餐饮消费者行为研究[J]. 人文地理,2015,30(5):147-152.
[5]蔡万坤. 中国餐饮市场的发展趋势及其对策[J]. 旅游学刊,2004,19(4):63-68.
[6]范秀成,李建州. 顾客餐馆体验的实证研究[J]. 旅游学刊,2006,21(3):56-61.
[7]张旭,徐逸伦. 南京市餐饮设施空间分布及其影响因素研究[J]. 热带地理,2009,29(4):362-367.
[8]李萍,陈田,王甫园,等. 基于文本挖掘的城市旅游社区形象感知研究——以北京市为例[J]. 地理研究,2017,36(6):1106-1122.
[9]于鹏,张宏梅,黄薇薇. 韩国旅游形象研究:基于韩国旅游发展局新浪微博的内容分析[J]. 安徽师范大学学报(自然科学版),2015,38(4):377-383.
[10]冯捷蕴. 北京旅游目的地形象的感知——中西方旅游者博客的多维话语分析[J]. 旅游学刊,2011,26(9):19-28.
[11]郭风华,王琨,张建立,等. 成都“五朵金花”乡村旅游地形象认知——基于博客游记文本的分析[J]. 旅游学刊,2015,30(4):84-94.
[12]CHENG M,XIN J. What do Airbnb users care about?An analysis of online review comments[J]. International journal of hospitality management,2019,76:58-70.
[13]KIM S,LEE W S. Network text analysis of medical tourism in newspapers using text mining:The South Korea case[J]. Tourism management perspectives,2019,31(1):332-339.
[14]周李,吴殿廷,虞虎,等. 基于网络游记的城市旅游流网络结构演化研究——以北京市为例[J]. 地理科学,2020,40(2):298-307.
[15]FANG B,YE Q,KUCUKUSTA D,et al. Analysis of the perceived value of online tourism reviews:influence of readability and reviewer characteristics[J]. Tourism management,2016,52:498-506.
[16]吴小根,杜莹莹. 旅游目的地游客感知形象形成机理与实证——以江苏省南通市为例[J]. 地理研究,2011,30(9):1554-1565.
[17]徐小波,赵磊,刘滨谊,等. 中国旅游城市形象感知特征与分异[J]. 地理研究,2015,34(7):1367-1379.
[18]彭丹,黄燕婷. 丽江古城旅游地意象研究:基于网络文本的内容分析[J]. 旅游学刊,2019,34(9):80-89.
[19]CELARDO L,EVERETT M G. Network text analysis:a two-way classification approach[J]. International journal of information management,2020,51:102009.
[20]刘逸,保继刚,陈凯琪. 中国赴澳大利亚游客的情感特征研究——基于大数据的文本分析[J]. 旅游学刊,2017,32(5):46-58.
[21]HU N,ZHANG T,GAO B,et al. What do hotel customers complain about? Text analysis using structural topic model[J]. Tourism management,2019,72:417-426.
[22]KIM K,PARK O J,YUN S,et al. What makes tourists feel negatively about tourism destinations?Application of hybrid text mining methodology to smart destination management[J]. Technological forecasting and social change,2017,123:362-369.
[23]AININ S,FEIZOLLAH A,ANUAR N B,et al. Sentiment analyses of multilingual tweets on halal tourism[J]. Tourism management perspectives,2020,34:100658.
[24]MANSOUR S. Social media analysis of user’s responses to terrorism using sentiment analysis and text mining[J]. Procedia computer science,2018,140:95-103.
[25]赵振斌,党娇. 基于网络文本内容分析的太白山背包旅游行为研究[J]. 人文地理,2011,26(1):134-139.
[26]GODNOV U,REDEK T. Application of text mining in tourism:case of Croatia[J]. Annals of tourism research,2016,58:162-166.
[27]张郴,黄震方,张捷,等. 基于机器学习的南京市旅游地个性及其文化景观表征[J]. 地理学报,2017,72(10):1886-1903.
[28]ZHANG C,HUANG Z F,CAO F,et al. Recognise me from outside to inside:learning the influence chain of urban destination personalities[J]. Tourism management,2019,70:390-403.
[29]张郴,黄震方. 旅游地三元空间交互理论模型建构[J]. 地理研究,2020,39(2):232-242.
[30]中国国家标准化管理委员会. 中华人民共和国国家标准:旅游业基础术语(GB/T 16766—2010)[S/OL]. [2021-08-06]. http://www.cnta.gov.cn.
[31]曾璇,崔海山,刘志根. 广州市餐饮店分布演变特征与影响因素[J]. 经济地理,2019,39(3):143-151.
[32]马斌斌,陈兴鹏,陈芳婷,等. 中华老字号企业空间分异及影响因素研究[J]. 地理研究,2020,39(10):2313-2329.
[33]KWON W,LEE M,BACK K J. Exploring the underlying factors of customer value in restaurants:a machine learning approach[J]. International journal of hospitality management,2020,91:102643.
[34]MIAO Q L,LI Q D,ZENG D. Fine-grained opinion mining by integrating multiple review sources[J]. Journal of the American society for information science and technology,2010,61(11):2288-2299.
[35]李君轶,任涛,陆路正. 游客情感计算的文本大数据挖掘方法比较研究[J]. 浙江大学学报(理学版),2020,47(4):507-520.

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备注/Memo

备注/Memo:
收稿日期:2021-08-11.
基金项目:国家自然科学基金项目(41871141、41301145、42071175).
通讯作者:张郴,博士,副教授,研究方向:旅游市场与城市旅游. E-mail:zhangc@njnu.edu.cn
更新日期/Last Update: 1900-01-01