A Context-Aware Recommendation System to Behavioral Based Authentication in Mobile and Pervasive Environments

2011 ◽  
Author(s):  
Joao Carlos D. Lima ◽  
Cristiano C. Rocha ◽  
Iara Augustin ◽  
M´rio A.R. Dantas
Keyword(s):  
Recommendation System ◽  
Context Aware ◽  
Pervasive Environments

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.

Integrating Context-aware Pervasive Environments

2006 ◽  
Author(s):  
Muhammad Khan ◽  
Kashif Zia ◽  
Nadeem Daudpota ◽  
S Hussain ◽  
Najma Taimoor
Keyword(s):  
Context Aware ◽  
Pervasive Environments

A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System

2018 ◽  
Vol 9 (4) ◽  
pp. 38-51
Author(s):  
Maryam Jallouli ◽  
Sonia Lajmi ◽  
Ikram Amous
Keyword(s):  
Social Network ◽  
Recommender System ◽  
Recommendation System ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
User Model ◽  
Context Aware ◽  
Additional Information ◽  
Context Element ◽  
Cold Start Problem

In the last decade, social-based recommender systems have become the best way to resolve a user's cold start problem. In fact, it enriches the user's model by adding additional information provided from his social network. Most of those approaches are based on a collaborative filtering and compute similarities between the users. The authors' preliminary objective in this work is to propose an innovative context aware metric between users (called contextual influencer user). These new similarities are called C-COS, C-PCC and C-MSD, where C refers to the category. The contextual influencer user model is integrated into a social based recommendation system. The category of the items is considered as the most pertinent context element. The authors' proposal is implemented and tested within the food dataset. The experimentation proved that the contextual influencer user measure achieves 0.873, 0.874, and 0.882 in terms of Mean Absolute Error (MAE) corresponding to C-cos, C-pcc and C-msd, respectively. The experimental results showed that their model outperforms several existing methods.

CAPRIOv2.0: A Context-Aware Unified Indoor-Outdoor Path Recommendation System

2020 ◽  
Author(s):  
Constantinos Costa ◽  
Xiaoyu Ge ◽  
Evan McEllhenney ◽  
Evan Kebler ◽  
Panos K. Chrysanthis ◽  
...  
Keyword(s):  
Recommendation System ◽  
Context Aware

scholarly journals Autonomic Semantic-Based Context-Aware Platform for Mobile Applications in Pervasive Environments

2016 ◽  
Vol 8 (4) ◽  
pp. 48 ◽  
Author(s):  
Adel Alti ◽  
Abderrahim Lakehal ◽  
Sébastien Laborie ◽  
Philippe Roose
Keyword(s):  
Mobile Applications ◽  
Context Aware ◽  
Pervasive Environments
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