Friend's recommendation on social media using different algorithms of machine learning
Ruksar Parveen,N. Sandeep Varma +1 more
- Vol. 2, Iss: 2, pp 273-281
TLDR
Friends Recommendation System identifies the behavior of users found in the dataset like user having number of followers, number of followings, common friends between followers and followings and provides the friend suggestions for the users they can follow.Abstract:
Friends Recommendation System identifies the behavior of users found in the dataset like user having number of followers, number of followings, common friends between followers and followings and provides the friend suggestions for the users they can follow. Recommendation system can also be used in other areas like recommending webpages to users in searching engines like Google, Explorer, Microsoft Edge. Recommending music in wynk, video recommendation in you tube, movie recommendation in amazon prime, recommendation of products to purchase in e-commerce applications like Flipkart, Amazon. Machine learning is used for providing recommendation on social networking application like Facebook, Instagram, Twitter Etc., In this Paper, recommendation of friends is done for Facebook. Similarity Coefficient calculations can be done using Jaccard Distance, Cosine Distance. Ranking Measures are done using Page Rank. Measuring the F1-Score and comparing the accuracy of different machine learning algorithms. These helps in finding which algorithm is more accurate in providing friends recommendations in social media recommendation system.read more
Citations
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Proceedings ArticleDOI
Friend Recommendation System in a Social Network based on Link Prediction Framework using Deep Neural Network
TL;DR: A personalized friend recommendation system based on a hybrid model that combines link prediction (which is a widely used traditional method in most social media platforms and follows the friend-of-friend approach) with a neural network model for added accuracy and efficiency, is discussed.
Journal ArticleDOI
HCoF: Hybrid Collaborative Filtering Using Social and Semantic Suggestions for Friend Recommendation
Mahesh Thyluru Ramakrishna,Vinoth Kumar Venkatesan,Rajat Bhardwaj,Surbhi Bhatia,Mohammad Khalid Imam Rahmani,Saima Anwar Lashari,Aliaa Mahfooz Alabdali +6 more
TL;DR: In this article , a new hybrid collaborative filtering (HCoF) approach amalgamates the social and semantic suggestions to enhance the performance of the recommendation to a high rate, and the mean precision of 0.503 was obtained by HCoF recommendation with semantic and social information.
Proceedings ArticleDOI
Study and Evaluation of Machine Learning algorithms for Aerospace applications
Isha Jain,M. J. +1 more
TL;DR: In this paper , an effort is made to explore, design and evaluate eleven machine learning algorithms for four aerospace applications: O-ring failure prediction (classification and regression), Airfoil self noise prediction test (regression), Dynamics test, Regression and steel plate fault detection.
Proceedings ArticleDOI
Anti-FakeU: Defending Shilling Attacks on Graph Neural Network based Recommender Model
TL;DR: Zhang et al. as mentioned in this paper constructed a user-user graph to capture the patterns of malicious behaviors and designed a novel GNN-based detector to identify fake users, and developed a data augmentation strategy and joint learning paradigm to train the recommender model and the proposed detector.
Journal ArticleDOI
Implementation of a Collaborative Recommendation System Based on Multi-Clustering
Lili Wang,Sunit Mistry,Abdulkadir Abdulahi Hasan,Abdiaziz Omar Hassan,Yousuf Islam,Frimpong Atta Junior Osei +5 more
TL;DR: In this paper , the authors present an architecture for a recommendation system based on user items that are transformed into narrow categories and the recommendation system focuses on the shortest connections between item correlations.
References
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