A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Study of Security Mechanisms to Create a Secure Cloud in a Virtual Environment with the Support of Cloud Service Providers
Volume-2 | Issue-3
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach
Volume-3 | Issue-3
Secure and Optimized Cloud-Based Cyber-Physical Systems with Memory-Aware Scheduling Scheme
Volume-2 | Issue-3
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks
Volume-3 | Issue-3
Computer Vision on IOT Based Patient Preference Management System
Volume-2 | Issue-2
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique
Volume-3 | Issue-4
Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security
Volume-4 | Issue-3
Design an Early Detection and Classification for Diabetic Retinopathy by Deep Feature Extraction based Convolution Neural Network
Volume-3 | Issue-2
Design of an Intelligent Approach on Capsule Networks to Detect Forged Images
Volume-3 | Issue-3
Future Challenges of the Internet of Things in the Health Care Domain - An Overview
Volume-3 | Issue-4
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
Volume - 3 | Issue - 1 | march 2021
Published
10 April, 2021
As the technology revolving around IoT sensors develops in a rapid manner, the subsequent social networks that are essential for the growth of the system will be utilized as a means to filter the objects that are preferred by the consumers. The ultimate purpose of the system is to give the customers personalized recommendations based on their preference. Similarly, the location and orientation will also play a crucial role in identifying the preference of the customer is a more efficient manner. Almost all social networks make use of location information to provide better services to the users based on the research performed. Hence there is a need for developing a recommender system that is dependent on location. In this paper, we have incorporated a recommender system that makes use of recommender algorithm that is personalized to take into consideration the context of the user. The preference of the user is analysed with the help of IoT smart devices like the smart watches, Google home, smart phones, ipads etc. The user preferences are obtained from these devices and will enable the recommender system to gauge the best resources. The results based on evaluation are compared with that of the content-based recommender algorithm and collaborative filtering to enable the recommendation engine’s power.
KeywordsIoT devices orientation context context awareness social networks recommender system
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