Notice Board :

Call for Paper
Vol. 5 Issue 9

Submission Start Date:
September 01, 2019

Acceptence Notification Start:
September 10, 2019

Submission End:
September 15, 2019

Final MenuScript Due:
September 25, 2019

Publication Date:
September 30, 2019


                         Notice Board: Call for PaperVol. 5 Issue 9      Submission Start Date: September 01, 2019      Acceptence Notification Start: September 10, 2019      Submission End: September 15, 2019      Final MenuScript Due: September 25, 2019      Publication Date: September 30, 2019




Volume V Issue VI

Author Name
Neha Kale, Mohit Jain
Year Of Publication
2019
Volume and Issue
Volume 5 Issue 6
Abstract
Recommender Systems (RS) are widely used for providing automatic personalized suggestions for information, products and services. Collaborative Filtering (CF) is one of the most popular recommendation techniques. However, with the rapid growth of the Web in terms of users and items, majority of the RS using CF technique suffer from problems like data sparsity and scalability. In this paper, we present a Recommender System based on data clustering techniques to deal with the scalability problem associated with the recommendation task. We use different voting systems as algorithms to combine opinions from multiple users for recommending items of interest to the new user.
PaperID
2019/IJRRETAS/6/2019/39697

Author Name
Mukesh Choudhary, Mohit Jain
Year Of Publication
2019
Volume and Issue
Volume 5 Issue 6
Abstract
Base64 encoding is a process of converting binary data to an ASCII string format by converting that binary data into a 6-bit character representation. The Base64 method of encoding is used when binary data, such as images or video, needs to be transmitted over systems that are designed only to transmit data in a plain text (ASCII) format. Web developers use base64 formats to include images, fonts, sounds and other resources directly inside HTML, JavaScript, JSON and XML files. We estimate that billions of base64 messages are decoded every day.
PaperID
2019/IJRRETAS/6/2019/39694

Author Name
Sonal Jain, Mohit Jain
Year Of Publication
2019
Volume and Issue
Volume 5 Issue 6
Abstract
Big data is used to store bulk amount of data. Hadoop processing system involves large data to deal with and offers scalable and distributed storage. In every minutes and seconds, large data is generated, with the generation of large data they required to be store in a safe and secure manner. As data, leakage is common in Hadoop Distributed File System so security methods need to be implemented in scenario. Existing work uses ARIA and AES algorithm and faces the issue of memory overheads and extra computation time.
PaperID
2019/IJRRETAS/6/2019/39693