An Ontology-based Context awareness for Smart Tourism Recommendation System

2018 ◽  
Author(s):  
Hajar Khallouki ◽  
Ahmed Abatal ◽  
Mohamed Bahaj
Keyword(s):  
Context Awareness ◽  
Recommendation System ◽  
Smart Tourism

Using RSSI Simple Localization Method to Implement the Context-Aware and Social Recommendation System

2013 ◽  
Vol 479-480 ◽  
pp. 1213-1217
Author(s):  
Mu Yen Chen ◽  
Ming Ni Wu ◽  
Hsien En Lin
Keyword(s):  
Social Media ◽  
Social Relations ◽  
Context Awareness ◽  
Recommendation System ◽  
Product Information ◽  
Indoor Localization ◽  
Context Aware ◽  
Social Recommendation ◽  
Localization Method ◽  
The Social

This study integrates the concept of context-awareness with association algorithms and social media to establish the Context-aware and Social Recommendation System (CASRS). The Simple RSSI Indoor Localization Module (SRILM) locates the user position; integrating SRILM with Apriori Recommendation Module (ARM) provides effective recommended product information. The Social Media Recommendation Module (SMRM) connects to users social relations, so that the effectiveness for users to gain product information is greatly enhanced. This study develops the system based on actual context.

scholarly journals Web-Based Recommendation System for Smart Tourism: Multiagent Technology

2019 ◽  
Vol 11 (2) ◽  
pp. 323 ◽  
Author(s):  
Raheleh Hassannia ◽  
Ali Vatankhah Barenji ◽  
Zhi Li ◽  
Habib Alipour
Keyword(s):  
Real Time ◽  
Web Application ◽  
Recommendation System ◽  
Online Communication ◽  
Data Communication ◽  
Tourism Industry ◽  
Time Data ◽  
Real Time Data ◽  
Hybrid Recommendation ◽  
Smart Tourism

The purpose of the study is to design and develop a recommended system based on agent and web technologies, which utilizes a hybrid recommendation filtering for the smart tourism industry. A hybrid recommendation system based on agent technology is designed by considering the online communication with other sectors in the tourism industry, such as the tourism supply chain, agency etc. However, online communication between the sectors via agents is designed and developed based on the contract net protocol. Furthermore, the design system is developed on the java agent development framework and implemented as a web application. Case study-based results considering two scenarios involving 100 customers illustrated that the proposed web application improves the rate of the recommendation for the customers. In the first scenario without disturbances, this rate was improved by 20% and the second scenario with disturbances yielded a 30% rate of acceptable recommendation. In addition, based on the second scenario, real time data communication on the system occurred, thus the proposed system supported real time data communication.

scholarly journals Recommendation System for Sightseeing Tours

2020 ◽  
Vol 4 (2) ◽  
pp. 34-54
Author(s):  
Ricardo Claudino Valadas ◽  
Elizabeth Simão Carvalho
Keyword(s):  
Context Awareness ◽  
Recommendation System ◽  
Response Times ◽  
External Application ◽  
Points Of Interest ◽  
Tourism Sector ◽  
Current Location ◽  
Application Programming ◽  
Programming Interfaces ◽  
Positive Results

This research proposes a model of a recommendation system (RS) for tourist itineraries. The RS suggests tips of what to visit in a city, based on the available time, personal preferences, current geo-location, and the user's context awareness. These suggestions are calculated based on the treatment of collected data in real time by external application programming interfaces, through a list of points of interest located within a radius that can be reached by the user. Preliminary tests validated the model's goals and its potential in the tourism sector. The RS for tourist itineraries proposed is based on four essential points, in order to make the experience different and well as possible: end-user's personal tastes, the time available, end-user's current location, and context awareness. The performance tests that were carried out brought very positive results and showed that the RS presented a number of requisitions proportional to the server response times and algorithm. The functionality tests were quite positive, with percentages of experience of using the RS between 62.5% and 100%.

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