Srikantaiah K.C

Work place: Department of Computer Science & Engineering, SJB Institute of Technology, Bengaluru, 560060, Karnataka, India



Research Interests: Computational Science and Engineering, Computer systems and computational processes, Computer Architecture and Organization, Data Mining, World Wide Web, Data Structures and Algorithms


Dr. Srikantaiah K C is currently a Professor in the Department of Computer Science and Engineering at S J B Institute of Technology, Bangalore, India. He obtained his B.E from Bangalore Institute of Technology, M.E from University Visvesvaraya College of Engineering, Bangalore in 2002 and Ph. D degree in Computer Science and Engineering from Bangalore University, Bangalore. He has authored a book on Web Mining Algorithms. His research interest is in the area of Data Mining, Web Mining, Big Data Analytics, Cloud Analytics and Semantic Web.

Author Articles
Personalized Recommendation Systems (PRES): A Comprehensive Study and Research Issues

By Raghavendra C K Srikantaiah K.C Venugopal K. R

DOI:, Pub. Date: 8 Oct. 2018

The type of information systems used to recommend items to the users are called Recommendation systems. The concept of recommendations was seen among cavemen, ants and other creatures too. Users often rely on opinion of their peers when looking for selecting something, this usual behavior of the humans, led to the development of recommendation systems. There exist various recommender systems for various areas. The existing recommendation systems use different approaches. The applications of recommendation systems are increasing with increased use of web based search for users’ specific requirements. Recommendation techniques are employed by general purpose websites such as google and yahoo based on browsing history and other information like user’s geographical locations, interests, behavior in the web, history of purchase and the way they entered the website.
Document recommendation systems recommend documents depending on the similar search done previously by other users. Clickstream data which provides information like user behavior and the path the users take are captured and given as input to document recommendation system. Movie recommendation systems and music recommendation systems are other areas in use and being researched to improve. Social recommendation is gaining the momentum because of huge volume of data generated and diverse requirements of the users. Current web usage trends are forcing companies to continuously research for best ways to provide the users with the suitable information as per the need depending on the search and preferences.
This paper throws light on common strategies being followed for building recommendation systems. The study compares existing techniques and highlights the opportunities available for research in this area.

[...] Read more.
Other Articles