Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
Volume-3 | Issue-2
Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Blockchain Framework for Communication between Vehicle through IoT Devices and Sensors
Volume-3 | Issue-2
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
A Review on Data Securing Techniques using Internet of Medical Things
Volume-3 | Issue-3
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
Maximizing the Prediction Accuracy in Tweet Sentiment Extraction using Tensor Flow based Deep Neural Networks
Volume-3 | Issue-2
Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
DDOS ATTACK DETECTION IN TELECOMMUNICATION NETWORK USING MACHINE LEARNING
Volume-1 | Issue-1
Gas Leakage Detection in Pipeline by SVM classifier with Automatic Eddy Current based Defect Recognition Method
Volume-3 | Issue-3
Design an Adaptive Hybrid Approach for Genetic Algorithm to Detect Effective Malware Detection in Android Division
Volume-3 | Issue-2
Comparison of Stock Price Prediction Models using Pre-trained Neural Networks
Volume-3 | Issue-2
Construction of a Framework for Selecting an Effective Learning Procedure in the School-Level Sector of Online Teaching Informatics
Volume-3 | Issue-4
Machine Learning Algorithms Performance Analysis for VLSI IC Design
Volume-3 | Issue-2
Efficient Two Stage Identification for Face mask detection using Multiclass Deep Learning Approach
Volume-3 | Issue-2
Characterizing WDT subsystem of a Wi-Fi controller in an Automobile based on MIPS32 CPU platform across PVT
Volume-2 | Issue-4
Assimilation of IoT sensors for Data Visualization in a Smart Campus Environment
Volume-3 | Issue-4
Design of Data Mining Techniques for Online Blood Bank Management by CNN Model
Volume-3 | Issue-3
Ethereum and IOTA based Battery Management System with Internet of Vehicles
Volume-3 | Issue-3
Volume - 4 | Issue - 3 | september 2022
Published
15 September, 2022
Everyone has their own distinct musical preferences; it's safe to assume that each music will find an appreciative audience. It's important to note that there isn't a single human society that has ever survived without music. There are two major gains from this study. Initially, a multi-strategy approach is taken to develop hybrid recommendation algorithms that give more accuracy than the existing algorithms. Also this hybrid algorithm is used to find new music in real time. This allows the algorithm to make an educated guess as to which musician and song best suit the user. As a second step, a general context-aware and emotion-based customized music framework is offered to facilitate the quick growth of context-aware music recommendation systems and to shed light on the whole recommendation procedure. Multiple methods exist for responding to requests, and a general framework is required for both collecting these methods and interpreting them within the context of the proposed framework. The kind of recommendation algorithm used is decided by the format of the input.
KeywordsMusic recommender systems hybrid approach neural network emotion-aware context-awareness.
Full Article PDF Download Article PDF