most citedUser Profiling Trends, Techniques and Applications

50 citations · 140 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG201522 cited

A Survey of Classification Techniques in the Area of Big Data

Praful Koturwar, Sheetal Girase, Debajyoti Mukhopadhyay

Big Data concern large-volume, growing data sets that are complex and have multiple autonomous sources. Earlier technologies were not able to handle storage and processing of huge…

cs.IR201550 cited

Role of Matrix Factorization Model in Collaborative Filtering Algorithm: A Survey

Dheeraj kumar Bokde, Sheetal Girase, Debajyoti Mukhopadhyay

Recommendation Systems apply Information Retrieval techniques to select the online information relevant to a given user. Collaborative Filtering is currently most widely used appro…

cs.IR201550 cited

User Profiling Trends, Techniques and Applications

Sumitkumar Kanoje, Sheetal Girase, Debajyoti Mukhopadhyay

The Personalization of information has taken recommender systems at a very high level. With personalization these systems can generate user specific recommendations accurately and…

cs.IR201513 cited

An Item-Based Collaborative Filtering using Dimensionality Reduction Techniques on Mahout Framework

Dheeraj kumar Bokde, Sheetal Girase, Debajyoti Mukhopadhyay

Collaborative Filtering is the most widely used prediction technique in Recommendation System. Most of the current CF recommender systems maintains single criteria user rating in u…

cs.IR20155 cited

User Profiling for Recommendation System

Sumitkumar Kanoje, Sheetal Girase, Debajyoti Mukhopadhyay

Recommendation system is a type of information filtering systems that recommend various objects from a vast variety and quantity of items which are of the user interest. This resul…