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An Efficient Approach of Travel Recommendation Model from High Dimensional Databases – A Survey

S. P. Gayathri
2018 International Journal for Research in Applied Science and Engineering Technology  
We obtain user-specific travel preferences from his/her travel history in one city and use these to recommend tourist locations in another city.  ...  personalized recommendations.  ...  The planning for tourist's trip various and unknown locations used personalized recommendation tourist locations and consider spatial, weather content for tourist.  ... 
doi:10.22214/ijraset.2018.4225 fatcat:girdkmqwnrf6vfwl3mxsxzcbem

Personalized location prediction for group travellers from spatial–temporal trajectories

Elahe Naserian, Xinheng Wang, Keshav Dahal, Zhi Wang, Zaijian Wang
2018 Future generations computer systems  
To achieve this goal, we propose a new group pattern discovery approach to extract the travel groups from spatial-temporal trajectories of users.  ...  Existing studies on this topic mostly focus on individual movements, considering the trajectories as solo movements. However, a user usually does not visit locations just for the personal interest.  ...  Accordingly, we proposed a novel personalized prediction framework to predict the next location of a user for applications such as location-based services.  ... 
doi:10.1016/j.future.2018.01.024 fatcat:6xqlobf4nngqbir2qo4wzjzxma

Theme issue on adaptation and personalization for ubiquitous computing

Zhiwen Yu, Doreen Cheng, Ismail Khalil, Judy Kay, Dominikus Heckmann
2011 Personal and Ubiquitous Computing  
This theme issue aims to explore adaptation and personalization services and technologies for ubiquitous computing.  ...  It proposes recommending a social itinerary by learning from multiple user-generated digital trails, such as GPS trajectories of residents and travel experts.  ...  The last paper, ''Generating recommendations for consensus negotiation in group personalization services'', by Maria Salamó, Kevin McCarthy, and Barry Smyth investigates group personalization services  ... 
doi:10.1007/s00779-011-0441-x fatcat:5c57r5ua6bfx3eayxhh6b2gaue

Research on Precision Marketing Model of Tourism Industry Based on User's Mobile Behavior Trajectory

Jialin Zhang, Tong Wu, Zhipeng Fan
2019 Mobile Information Systems  
Data mining clustering technology is used to analyze the characteristics of users' mobile behavior trajectories, and the precise recommendation system of tourism is constructed to provide support for tourism  ...  It can target the tourist group for precise marketing and make tourists travel smarter.  ...  mobile behavior trajectory and extract useful information from the user's mobile behavior trajectory data is very important for the realization of personalized recommendation service.  ... 
doi:10.1155/2019/6560848 fatcat:7bov7gmtkfhnxeeqfv2xdnrbkq

Creating Personalized Recommendations in a Smart Community by Performing User Trajectory Analysis through Social Internet of Things Deployment

Guang Xing Lye, Wai Khuen Cheng, Teik Boon Tan, Chen Wei Hung, Yen-Lin Chen
2020 Sensors  
For the aforementioned reasons, this paper presents an SIoT architecture with a personalized recommendation framework to enhance service discovery and composition.  ...  The novel contribution of this study is the development of a unique personalized recommender engine that is based on the knowledge–desire–intention model and is suitable for service discovery in a smart  ...  Deep learning can be used to model SIoT behaviors for delivering suitable recommendations in service discovery and composition.  ... 
doi:10.3390/s20072098 pmid:32276431 pmcid:PMC7181154 fatcat:nflvgee54ze6rox2bbxlogiryi


2013 International Journal of Information Technology and Decision Making  
The techniques like graph-based similarity computations 37,121 and matrix factorizations, 61,81,109 are often used for collaborative¯lterings.  ...  For avoiding certain limitations, hybrid approaches which combine content-based methods and collaborative¯lterings are widely used. 66 For example, the performance of matrix factorization-based collaborative  ...  Lu and Tseng 79 proposed a Personal Mobile Commerce Pattern Mine (PMCP-Mine) algorithm for e±cient discovery of mobile users' Personal Mobile Commerce Patterns (PMCPs).  ... 
doi:10.1142/s0219622013500077 fatcat:q7fvqibeonaz3nwah6s5t4pfhy

Recommendations in location-based social networks: a survey

Jie Bao, Yu Zheng, David Wilkie, Mohamed Mokbel
2015 Geoinformatica  
We discuss the new properties and challenges that location brings to recommender systems for LBSNs.  ...  This addition of vast geo-spatial datasets has stimulated research into novel recommender systems that seek to facilitate users' travels and social interactions.  ...  User interaction patterns in LBSNs include user tags and commenting patterns. The user interaction patterns are used for friend recommendation and community discovery systems, e.g. as in [38, 104] .  ... 
doi:10.1007/s10707-014-0220-8 fatcat:3ivmtrnvkfhshl72gd33h4aola

Big Trajectory Data Mining: A Survey of Methods, Applications, and Services

Di Wang, Tomio Miwa, Takayuki Morikawa
2020 Sensors  
Finally, we briefly discuss the services that can be developed from studies in this field. Practical implications are also delivered for participants in trajectory data mining.  ...  The development of data mining and analysis methods has allowed researchers to use these trajectory datasets to identify urban reality (e.g., citizens' collective behavior) in order to solve urban problems  ...  behavior, travel patterns, and other aspects.  ... 
doi:10.3390/s20164571 pmid:32824028 pmcid:PMC7472055 fatcat:bgav5exs3nejhp42bbakf3ftp4

Trajectory data mining: A review of methods and applications

Jean Damascène Mazimpaka, Sabine Timpf
2016 Journal of Spatial Information Science  
As a result, researchers devoted their efforts to developing analysis methods including different data mining methods for trajectories.  ...  The increasing use of location-aware devices has led to an increasing availability of trajectory data.  ...  They also would like to thank the anonymous reviewers for their comments that helped to improve the paper.  ... 
doi:10.5311/josis.2016.13.263 fatcat:cuxgsxpslfeunehzawbgctu4r4

A Survey on Trajectory Data Mining: Techniques and Applications

Zhenni Feng, Yanmin Zhu
2016 IEEE Access  
This framework and the survey can be used as a guideline for designing future trajectory data mining solutions. INDEX TERMS Trajectory data mining, big data applications, data mining techniques.  ...  In this paper, we survey various applications of trajectory data mining, e.g., path discovery, location prediction, movement behavior analysis, and so on.  ...  Discovery of movement patterns is crucial for understanding human behavior.  ... 
doi:10.1109/access.2016.2553681 fatcat:bwz3c6oyfjahroihps7i3wo76q

Discovering Travel Community for POI Recommendation on Location-Based Social Networks

Lei Tang, Dandan Cai, Zongtao Duan, Junchi Ma, Meng Han, Hanbo Wang
2019 Complexity  
Point-of-interest (POI) recommendations are a popular form of personalized service in which users share their POI location and related content with their contacts in location-based social networks (LBSNs  ...  The similarity and relatedness between users of the same POI type are frequently used for trajectory retrieval, but most of the existing works rely on the explicit characteristics from all users' check-in  ...  service that can greatly enhance the travel experience of users [4, 5] .  ... 
doi:10.1155/2019/8503962 fatcat:a5y6gp2mmjbezeoqmu3ojz2mla

Making tourist guidance systems more intelligent, adaptive and personalised using crowd sourced movement data

Anahid Basiri, Pouria Amirian, Adam Winstanley, Terry Moore
2017 Journal of Ambient Intelligence and Humanized Computing  
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution  ...  mining techniques and use the recognised patterns and PoI in more personalised, adaptive and intelligent recommender and suggestion making services.  ...  For example, the support for suggestion X is increasing. This form of rule is particularly useful for temporal and spatio-temporal knowledge discovery.  ... 
doi:10.1007/s12652-017-0550-0 fatcat:xbd2xj3nivfd7bi7kcnaqgkaqy

Recommendation for Ridesharing Groups Through Destination Prediction on Trajectory Data

Lei Tang, Zongtao Duan, Yishui Zhu, Junchi Ma, Zihang Liu
2019 IEEE transactions on intelligent transportation systems (Print)  
We first developed a PrefixSpan-prediction using a partial matching (P-PPM) destination-prediction algorithm to mine the frequent movement patterns from the trajectory data and determine the confidence  ...  In this paper, we aim to provide an optimal passenger matching solution by recommending ridesharing groups of passengers from GPS trajectories.  ...  knowledge from the universal model to personalize the recommendation for every individual in an online learning manner.  ... 
doi:10.1109/tits.2019.2961170 fatcat:dkqilcyni5axdgqf4pfq4pnfhy

Driving with knowledge from the physical world

Jing Yuan, Yu Zheng, Xing Xie, Guangzhong Sun
2011 Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11  
As a result, our service accurately estimates the travel time of a route for a user; hence finding the fastest route customized for the user.  ...  Using this model, our system predicts the traffic conditions of a future time (when the computed route is actually driven) and performs a self-adaptive driving direction service for a particular user.  ...  Smart Routing To optimize taxi drivers' income, literatures [7] [19] has proposed route recommendation services for a taxi driver by analyzing fleet trajectories.  ... 
doi:10.1145/2020408.2020462 dblp:conf/kdd/YuanZXS11 fatcat:gsm75aexobdxzhcm3xosb6lbjy

Travel topic analysis: a mutually reinforcing method for geo-tagged photos

Ngai Meng Kou, Leong Hou U, Yiyang Yang, Zhiguo Gong
2015 Geoinformatica  
Such travel topics can be used in different applications, such as advertisements, promotion strategies, and city planning.  ...  Sharing personal activities on social networks is very popular nowadays, where the activities include updating status, uploading dining photos, sharing video clips, etc.  ...  FP-Growth is an efficient method for mining frequent patterns and LDA is another widely accepted method in topic discovery problems. We randomly select 10% trajectories as the testing data.  ... 
doi:10.1007/s10707-015-0226-x fatcat:faruakt7hzgbdk5dv5wtqg26yu
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