出行决策建模的预测分析

R. Keerthi, P. Lakshmi
{"title":"出行决策建模的预测分析","authors":"R. Keerthi, P. Lakshmi","doi":"10.1109/ICGCIOT.2018.8753103","DOIUrl":null,"url":null,"abstract":"The exponential rise in technologies has opened up a gigantic scope to exploit the data for better decision making. The evolution of social media has contributed humungous information including ratings, reviews and comments. Considering the significance of an efficient predictive analysis model for the tourist destination prediction, in the proposed work robust technologies have been applied to perform the destination prediction. This work contributes to the technique of developing a novel Destination Prediction Model that corresponds to the tourist’s preferences.","PeriodicalId":269682,"journal":{"name":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predictive Analysis for Modeling Travel Decision Making\",\"authors\":\"R. Keerthi, P. Lakshmi\",\"doi\":\"10.1109/ICGCIOT.2018.8753103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The exponential rise in technologies has opened up a gigantic scope to exploit the data for better decision making. The evolution of social media has contributed humungous information including ratings, reviews and comments. Considering the significance of an efficient predictive analysis model for the tourist destination prediction, in the proposed work robust technologies have been applied to perform the destination prediction. This work contributes to the technique of developing a novel Destination Prediction Model that corresponds to the tourist’s preferences.\",\"PeriodicalId\":269682,\"journal\":{\"name\":\"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)\",\"volume\":\"102 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICGCIOT.2018.8753103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Second International Conference on Green Computing and Internet of Things (ICGCIoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICGCIOT.2018.8753103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

技术的指数级增长为利用数据做出更好的决策开辟了一个巨大的空间。社交媒体的发展提供了大量的信息,包括评分、评论和评论。考虑到有效的预测分析模型对旅游目的地预测的重要性,本文采用鲁棒技术进行目的地预测。这项工作有助于开发一种符合游客偏好的新型目的地预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Analysis for Modeling Travel Decision Making
The exponential rise in technologies has opened up a gigantic scope to exploit the data for better decision making. The evolution of social media has contributed humungous information including ratings, reviews and comments. Considering the significance of an efficient predictive analysis model for the tourist destination prediction, in the proposed work robust technologies have been applied to perform the destination prediction. This work contributes to the technique of developing a novel Destination Prediction Model that corresponds to the tourist’s preferences.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信