DocumentCode :
3659547
Title :
A hybrid approach for recommendation system with added feedback component
Author :
Kavinkumar V.;Rachamalla Rahul Reddy;Rohit Balasubramanian; Sridhar M.; Sridharan K.;D. Venkataraman
Author_Institution :
Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham (University), India
fYear :
2015
Firstpage :
745
Lastpage :
752
Abstract :
With the increasing E-Commerce and online shopping there is a need for recommendation systems which help the customers in decision making and to suggest potential goods of purchase. In domains such as automobiles there are many websites but most of them are not having enhanced recommendation systems to enable easy decision making. Thus we have taken the initiative of building a dataset with multiple parameters based on a survey of the communities needs using potential blogs and created a recommendation system using user based and item based collaborative filtering. In addition to the combined collaborative filtering techniques we propose a framework which includes a feedback analysis to improve the recommendation system. The enhanced model aids the customers in decision making. We have proposed the feedback system at two levels. One is external feedback where the comments are gathered from public platforms like social media and automobile websites. The other is internal feedback i.e. the feedback is taken from users who have been provided with recommended items. The opinions extracted from such varied comments broadens the system and results. Our proposed hybrid model with feedback analysis has improvised the current system by providing better suggestions to customers.
Keywords :
"Collaboration","Filtering","Feature extraction","Principal component analysis","Automobiles","Algorithm design and analysis","Media"
Publisher :
ieee
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on
Print_ISBN :
978-1-4799-8790-0
Type :
conf
DOI :
10.1109/ICACCI.2015.7275700
Filename :
7275700
Link To Document :
بازگشت