{"title":"Tour-sites Recommendation Mechanism for Navigation System","authors":"C. Chou, Sheng-Tzong Cheng, Yi Tsen Chiang","doi":"10.3966/160792642019012001011","DOIUrl":null,"url":null,"abstract":"This work proposed a hierarchical tour-sites recommendation mechanism based on tourist group which is context, location, and time awareness. This mechanism includes two parts, Inter-site and Intra-site. We adopted the Artificial Fish Swarm Algorithm (AFSA) to build this two parts tour-sites recommendation mechanism. In the Inter-site recommendation, we combined Co-occurrence concept to predict the interest of tourists. We formulate the problem of choosing the paths among the vehicles in the same region by using non-cooperative game theory, and find out the solution of this game which is known as Nash equilibrium. This mechanism determined on reducing the average waiting time of tourist and balancing the congestion degree of sites in a city and presents a recommendation mechanism for vehicle-sharing. Moreover, it took the demand of tourists into consideration. The experimental results showed that the mechanism we proposed improve the tourism experience for tourist groups.","PeriodicalId":50172,"journal":{"name":"Journal of Internet Technology","volume":"20 1","pages":"123-133"},"PeriodicalIF":0.9000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Internet Technology","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3966/160792642019012001011","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1
Abstract
This work proposed a hierarchical tour-sites recommendation mechanism based on tourist group which is context, location, and time awareness. This mechanism includes two parts, Inter-site and Intra-site. We adopted the Artificial Fish Swarm Algorithm (AFSA) to build this two parts tour-sites recommendation mechanism. In the Inter-site recommendation, we combined Co-occurrence concept to predict the interest of tourists. We formulate the problem of choosing the paths among the vehicles in the same region by using non-cooperative game theory, and find out the solution of this game which is known as Nash equilibrium. This mechanism determined on reducing the average waiting time of tourist and balancing the congestion degree of sites in a city and presents a recommendation mechanism for vehicle-sharing. Moreover, it took the demand of tourists into consideration. The experimental results showed that the mechanism we proposed improve the tourism experience for tourist groups.
本文提出了一种基于游客群体语境、地点和时间意识的分级旅游景点推荐机制。该机制包括站点间机制和站点内机制两部分。我们采用人工鱼群算法(Artificial Fish Swarm Algorithm, AFSA)构建了这个由两部分组成的旅游站点推荐机制。在站点间推荐中,我们结合Co-occurrence的概念来预测游客的兴趣。利用非合作博弈理论,提出了同一区域内车辆的路径选择问题,并求出了该博弈的解,即纳什均衡。该机制以减少游客的平均等待时间和平衡城市站点的拥堵程度为目标,提出了一种车辆共享的推荐机制。此外,它考虑到游客的需求。实验结果表明,本文提出的机制改善了旅游团的旅游体验。
期刊介绍:
The Journal of Internet Technology accepts original technical articles in all disciplines of Internet Technology & Applications. Manuscripts are submitted for review with the understanding that they have not been published elsewhere.
Topics of interest to JIT include but not limited to:
Broadband Networks
Electronic service systems (Internet, Intranet, Extranet, E-Commerce, E-Business)
Network Management
Network Operating System (NOS)
Intelligent systems engineering
Government or Staff Jobs Computerization
National Information Policy
Multimedia systems
Network Behavior Modeling
Wireless/Satellite Communication
Digital Library
Distance Learning
Internet/WWW Applications
Telecommunication Networks
Security in Networks and Systems
Cloud Computing
Internet of Things (IoT)
IPv6 related topics are especially welcome.