Notice Board :

Call for Paper
Vol. 4 Issue 11

Submission Start Date:
November 01, 2018

Acceptence Notification Start:
November 10, 2018

Submission End:
November 15, 2018

Final MenuScript Due:
November 25, 2018

Publication Date:
November 30, 2018


                         Notice Board: Call for PaperVol. 4 Issue 11      Submission Start Date: November 01, 2018      Acceptence Notification Start: November 10, 2018      Submission End: November 15, 2018      Final MenuScript Due: November 25, 2018      Publication Date: November 30, 2018




Volume III Issue VI

Author Name
Khushboo Sahu, Prof. Mayank Bhatt
Year Of Publication
2017
Volume and Issue
Volume 3 Issue 6
Abstract
A recommendation engine is a feature (not a product) that filters items by predicting how a user might rate them. It solves the problem of connecting your existing users with the right items in your massive inventory (i.e. tens of thousands to millions) of products or content. Product recommendations are a must-have feature for all ecommerce websites, as they can drive sales, increase conversion rate and order value. Sending personalized product recommendations to your customers increases sales in just a few clicks. Add a Product Recommendations content block or merge tag to E-commerce Automation workflows to encourage subscribers to visit your store, re-engage inactive customers by promoting relevant items, suggest your best-selling products to new customers, and much more. Most of web portals have integrated this feature but web personalization is still a demanding issue. This project works target to integrate web personalization feature with product recommendation to enhance the sal
PaperID
2017/IJRRETAS/6/2017/25610

Author Name
Diwakar Yadav, Prof. Megha Singh
Year Of Publication
2017
Volume and Issue
Volume 3 Issue 6
Abstract
Cloud computing is emerging at the following three major trends — service orientation, virtualization and standardization of computing through the Internet. Cloud computing enables users and developers to use services without knowledge of, nor control over the technology infrastructure that supports them. In this era, Private cloud is now became popular by achieving a great efficiency of resources as well as improved to manage IT resources and services within an enterprise or organization. Cloud Storage is an attractive concept in IT field since it allows the resources to be provisioned according to the user needs. In private cloud resources are provided over intranet within an organization. In the studied research paper the implementation steps of private cloud are given. In this Paper, first we have to establish a private cloud and then we are going to measure the performance factors that is CPU , Memory Usage using System monitoring tools so that it gives the better evaluation unde
PaperID
2017/IJRRETAS/6/2017/25611

Author Name
Arpita Yadav, Kapil Sahu
Year Of Publication
2017
Volume and Issue
Volume 3 Issue 6
Abstract
Several fields of science and technology are adopting Artificial Intelligence as an effective tool in complex and overwhelmingly large data analysis. One such field is prediction problems where statistical prediction prove to be too complex to handle or are not highly accurate. In this paper, we devise a model for wind speed prediction based on the use of Artificial Neural Networks (ANN). Wind speed prediction plays an extremely critical role in generation of renewable generation of power and reducing the dependence on fossil fuels. Here the Levenberg-Marquardt algorithm is used which employs back propagation and hence attains lesser time of convergence and overall average error. The performance metrics chosen are Mean Square Error (MSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE).
PaperID
2017/IJRRETAS/6/2017/26610