Add to ORKGAbstract- A real world challenging task of an e-commerce application is to identify the needs of the active users based on user navigation patterns. Online navigation patterns are grown every day and extracting business intelligence is a challenging one. There are various personalized recommender systems have been proposed in the literature. In this paper we propose and analyse the performance of back propagation neural network model for personalized recommender system for better quality in terms of accuracy. The performance of an algorithm has been tested with different parameters with real world dataset for the performance benchmark. Index Terms- Business intelligence, Back propagation
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recommender systems are ubiquitous in the modern internet, where they help users find items they mig...
Recommender agents will personalise the shopping experience of e-commerce users. In addition, the sa...
The present study assesses the technique of back propagation neural networks to appraise the average...
Now a day’s recommendation systems are becoming more popular to recommend products for the individua...
A number of techniques have been proposed recently, which attempt to improve the generalization capa...
Abstract. This paper discusses the use of artificial neural networks, trained with patterns extracte...
The recommender system is an essential tool for companies and users. A successful recommender system...
Accuracy improvement is among the primary key research focuses in the area of recommender systems. T...
Accuracy improvement is among the primary key research focuses in the area of recommender systems. T...
Recently, many researches have been made to find the impact of human resources on firm performance. ...
Recommender Systems (RSs) are used to provide users with personalized item recommendations and help ...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recommender systems are ubiquitous in the modern internet, where they help users find items they mig...
Recommender agents will personalise the shopping experience of e-commerce users. In addition, the sa...
The present study assesses the technique of back propagation neural networks to appraise the average...
Now a day’s recommendation systems are becoming more popular to recommend products for the individua...
A number of techniques have been proposed recently, which attempt to improve the generalization capa...
Abstract. This paper discusses the use of artificial neural networks, trained with patterns extracte...
The recommender system is an essential tool for companies and users. A successful recommender system...
Accuracy improvement is among the primary key research focuses in the area of recommender systems. T...
Accuracy improvement is among the primary key research focuses in the area of recommender systems. T...
Recently, many researches have been made to find the impact of human resources on firm performance. ...
Recommender Systems (RSs) are used to provide users with personalized item recommendations and help ...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recently, recommender systems have been developed for a variety of domains. Recommender systems also...
Recommender systems are ubiquitous in the modern internet, where they help users find items they mig...