scholarly journals Towards building real-time, convenient route recommendation system for public transit

2016 ◽  
Author(s):  
Garvita Bajaj ◽  
Rachit Agarwal ◽  
Georgios Bouloukakis ◽  
Pushpendra Singh ◽  
Nikolaos Georgantas ◽  
...  
Keyword(s):  
Real Time ◽  
Recommendation System ◽  
Public Transit ◽  
Convenient Route ◽  
Route Recommendation

scholarly journals Design and Development of a Real-Time Optimal Route Recommendation System Using Big Data for Tourists in Jeju Island

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 506 ◽  
Author(s):  
Faisal Mehmood ◽  
Shabir Ahmad ◽  
DoHyeun Kim
Keyword(s):  
Big Data ◽  
Real Time ◽  
Recommendation System ◽  
Tourism Industry ◽  
Jeju Island ◽  
Third Party ◽  
User Preference ◽  
Optimal Route ◽  
Route Recommendation ◽  
Travel Route Recommendation

Nowadays researchers and engineers are trying to build travel route recommendation systems to guide tourists around the globe. The tourism industry is on the rise and it has attracted researchers to provide such systems for comfortable and convenient traveling. Mobile internet growth is increasing rapidly. Mobile data usage and traffic growth has increased interest in building mobile applications for tourists. This research paper aims to provide design and implementation of a travel route recommendation system based on user preference. Real-time big data is collected from Wi-Fi routers installed at more than 149 unique locations in Jeju Island, South Korea. This dataset includes tourist movement patterns collected from thousands of mobile tourists in the year 2016–2017. Data collection and analysis is necessary for a country to make public policies and development of the global travel and tourism industry. In this research paper we propose an optimal travel route recommendation system by performing statistical analysis of tourist movement patterns. Route recommendation is based on user preferences. User preference can vary over time and differ from one user to another. We have taken three main factors into consideration to the recommend optimal route i.e., time, distance, and popularity of location. Beside these factors, we have also considered weather and traffic condition using a third-party application program interfaces (APIs). We have classified regions into six major categories. Popularity of location can vary from season to season. We used a Naïve Bayes classifier to find the probability of tourists going to visit next location. Third-party APIs are used to find the longitude and latitude of the location. The Haversine formula is used to calculate the distance between unique locations. On the basis of these factors, we recommend the optimal route for tourists. The proposed system is highly responsive to mobile users. The results of this system show that the recommended route is convenient and allows tourists to visit maximum number of famous locations as compared to previous data.

A real-time personalized route recommendation system for self-drive tourists based on vehicle to vehicle communication

2014 ◽  
Vol 41 (7) ◽  
pp. 3409-3417 ◽  
Author(s):  
Long Liu ◽  
Jin Xu ◽  
Stephen Shaoyi Liao ◽  
Huaping Chen
Keyword(s):  
Real Time ◽  
Recommendation System ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Vehicle To Vehicle Communication ◽  
Route Recommendation

scholarly journals Phone-Based Restaurant Recommendation System by Using Position Information and Association Rules

2012 ◽  
Vol 6-7 ◽  
pp. 783-789
Author(s):  
Jian Feng Dong ◽  
Tian Yang Dong ◽  
Jia Jie Yao ◽  
Ling Zhang
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Association Rules ◽  
Recommendation System ◽  
Rapid Development ◽  
Smart Phone ◽  
Smart Phones ◽  
Location Information ◽  
Position Information ◽  
The Real

With the rapid development of smart-phone applications, how to make the ordering process via smart-phones more convenient and intelligent has become a hotspot. This paper puts forward a method of restaurant dish recommendation relying on position information and association rules. In addition, this paper has designed and developed a restaurant recommendation system based on mobile phone. The system would fetch the real-time location information via smart-phones, and provide customers personalized restaurant and dish recommendation service. According to the related applications, this system can successfully recommend the related restaurants and food information to customers.

Delivering Real-Time Information Services on Public Transit: A Framework

2017 ◽  
Vol 18 (10) ◽  
pp. 2642-2656 ◽  
Author(s):  
Tianyi Ma ◽  
Gianmario Motta ◽  
Kaixu Liu
Keyword(s):  
Real Time ◽  
Public Transit ◽  
Information Services ◽  
Real Time Information ◽  
Time Information

A Cross-Platform Blood Donation Application with a Real-Time, Intelligent, and Rational Recommendation System

2021 ◽  
Author(s):  
Md Rafat Jamader Maraz ◽  
Rashik Rahman ◽  
Md. Mehedi Ul Hasnain ◽  
Hasan Murad
Keyword(s):  
Real Time ◽  
Recommendation System ◽  
Blood Donation ◽  
Cross Platform

scholarly journals An Improved Social Media Analysis on 3 Layers: A Real Time Enhanced Recommendation System

2018 ◽  
Vol 9 (2) ◽  
Author(s):  
Mohamed Amine ◽  
Hicham AIT ◽  
Reda MOULOUKI ◽  
Saida NKIRI ◽  
Mohamed AZOUAZI
Keyword(s):  
Social Media ◽  
Real Time ◽  
Recommendation System ◽  
Media Analysis ◽  
Social Media Analysis

scholarly journals Demand Supply Oriented Taxi Suggestion System for Vehicular Social Networks with Fuel Charging Mechanism

2019 ◽  
pp. 38-44
Author(s):  
Selvi C ◽  
Keerthana D
Keyword(s):  
Data Mining ◽  
Real Time ◽  
Large Scale ◽  
Recommendation System ◽  
Important Research ◽  
Taxi Drivers ◽  
Charging Station ◽  
Gps Trajectories ◽  
Charging Mechanism ◽  
Supply Level

Data mining depends on large-scale taxi traces is an important research concepts. A vital direction for analyzing taxi GPS dataset is to suggest cruising areas for taxi drivers. The project first investigates the real-time demand-supply level for taxis, and then makes an adaptive tradeoff between the utilities of drivers and passengers for different hotspots. This project constructs a recommendation system by jointly considering the profits of both drivers and passengers. At last, the qualified candidates are suggested to drivers based on analysis. The project also provides a real-time charging station recommendation system for EV taxis via large-scale GPS data mining. By combining each EV taxi’s historical recharging actions and real-time GPS trajectories, the present operational state of each taxi is predicted. Based on this information, for an EV taxi requesting a recommendation, recommend a charging station that leads to the minimal total time before its recharging starts.

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