一种新的文化遗产增强环境感知路径推荐方法

F. Colace, M. D'arienzo, Angelo Lorusso, Marco Lombardi, D. Santaniello, Carmine Valentino
{"title":"一种新的文化遗产增强环境感知路径推荐方法","authors":"F. Colace, M. D'arienzo, Angelo Lorusso, Marco Lombardi, D. Santaniello, Carmine Valentino","doi":"10.1109/SMARTCOMP58114.2023.00071","DOIUrl":null,"url":null,"abstract":"The will to travel leads humans to discover new places and enjoy new adventures. However, tourists usually need help knowing what to visit and, avoiding time issues, in which order to explore several Points of Interest (POIs). In this field, new technologies can help tourists to improve their experiences and select the visiting path according to personal preferences. Therefore, the employment of Recommender Systems allows the personalization of the experience through the appropriate POIs’ selection. Moreover, RSs’ analysis could take advantage of contextual information that suits the personalization in the specific environment where the elaboration happens, providing users with even more specific and tailored paths. This paper aims to design personalized visiting paths combining a Context-Aware Recommender System (CARSs) and a mathematical model to maximize the number of visited POIs in the available time. The proposed approach is tested through a prototype, obtaining promising results.","PeriodicalId":163556,"journal":{"name":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Context Aware Paths Recommendation Approach for the Cultural Heritage Enhancement\",\"authors\":\"F. Colace, M. D'arienzo, Angelo Lorusso, Marco Lombardi, D. Santaniello, Carmine Valentino\",\"doi\":\"10.1109/SMARTCOMP58114.2023.00071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The will to travel leads humans to discover new places and enjoy new adventures. However, tourists usually need help knowing what to visit and, avoiding time issues, in which order to explore several Points of Interest (POIs). In this field, new technologies can help tourists to improve their experiences and select the visiting path according to personal preferences. Therefore, the employment of Recommender Systems allows the personalization of the experience through the appropriate POIs’ selection. Moreover, RSs’ analysis could take advantage of contextual information that suits the personalization in the specific environment where the elaboration happens, providing users with even more specific and tailored paths. This paper aims to design personalized visiting paths combining a Context-Aware Recommender System (CARSs) and a mathematical model to maximize the number of visited POIs in the available time. The proposed approach is tested through a prototype, obtaining promising results.\",\"PeriodicalId\":163556,\"journal\":{\"name\":\"2023 IEEE International Conference on Smart Computing (SMARTCOMP)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Smart Computing (SMARTCOMP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMARTCOMP58114.2023.00071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Smart Computing (SMARTCOMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMARTCOMP58114.2023.00071","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

旅行的意愿引导人类去发现新的地方,享受新的冒险。然而,游客通常需要帮助知道参观什么,避免时间问题,以便探索几个兴趣点(POIs)。在这一领域,新技术可以帮助游客改善体验,根据个人喜好选择游览路径。因此,使用推荐系统可以通过选择适当的poi来实现体验的个性化。此外,RSs的分析可以利用上下文信息,在细化发生的特定环境中适合个性化,为用户提供更具体和定制的路径。本文旨在结合上下文感知推荐系统(cars)和数学模型设计个性化的访问路径,以最大化在可用时间内访问的poi数量。通过样机对该方法进行了测试,取得了令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Context Aware Paths Recommendation Approach for the Cultural Heritage Enhancement
The will to travel leads humans to discover new places and enjoy new adventures. However, tourists usually need help knowing what to visit and, avoiding time issues, in which order to explore several Points of Interest (POIs). In this field, new technologies can help tourists to improve their experiences and select the visiting path according to personal preferences. Therefore, the employment of Recommender Systems allows the personalization of the experience through the appropriate POIs’ selection. Moreover, RSs’ analysis could take advantage of contextual information that suits the personalization in the specific environment where the elaboration happens, providing users with even more specific and tailored paths. This paper aims to design personalized visiting paths combining a Context-Aware Recommender System (CARSs) and a mathematical model to maximize the number of visited POIs in the available time. The proposed approach is tested through a prototype, obtaining promising results.
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