An Approach for Building Efficient and Accurate Social Recommender Systems using Individual Relationship Networks - 2017


Social recommender system, using social relation networks as further input to enhance the accuracy of ancient recommender systems, has become an necessary analysis topic. But, most existing strategies utilize the complete user relationship network with no thought to its huge size, sparsity, imbalance, and noise issues. This may degrade the efficiency and accuracy of social recommender systems. This study proposes a new approach to manage the complexity of adding social relation networks to recommender systems. Our method first generates a private relationship network (IRN) for each user and item by developing a unique fitting algorithm of relationship networks to control the connection propagation and contracting. We then fuse matrix factorization with social regularization and also the neighborhood model using IRN's to generate recommendations. Our approach is sort of general, and can additionally be applied to the item-item relationship network by switching the roles of users and items. Experiments on four datasets with different sizes, sparsity levels, and relationship types show that our approach can improve predictive accuracy and gain a better scalability compared with state-of-the-art social recommendation methods.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : A Novel Electricity Price Forecasting Approach Based on Dimension Reduction Strategy and Rough Artificial Neural Networks ABSTRACT: In deregulated energy markets, accurate electricity price forecasting (EPF)
PROJECT TITLE : A Two-Stage Transformer-Based Approach for Variable-Length Abstractive Summarization ABSTRACT: For variable-length abstractive summarization, this paper suggests a two-stage technique. The suggested approach
PROJECT TITLE : An Analytical Approach for Soil and Land Classification System using Image Processing ABSTRACT: Land mapping and classification have piqued the interest of experts in recent decades for a variety of reasons.
PROJECT TITLE : An Automated Machine Learning Approach for Smart Waste Management Systems ABSTRACT: This study shows how automated machine learning can be used to solve a real-world problem in a Smart Waste Management system.
PROJECT TITLE : Machine Learning Driven Approach Towards the Quality Assessment of Fresh Fruits Using Non-invasive Sensing ABSTRACT: Accurate moisture content (MC) information in fruits and vegetables in an automated manner might

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry