In today‟s world with the increasing e-commerce and online shopping involved recommendation systems have become a major part of decision making. 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 onus of building a dataset with multiple parameters based on a survey of the communities needs and created a recommendation system using user based and item based collaborative filtering. To take into account the vast majority of people and their opinions we have added internal and external feedback analysis. Feedback analysis is the classification of textual data (comments) and analyzing the sentiment derived from it. We have proposed it at two levels external that is gathering comments from public platforms social media and automobile websites and internal i. e. the feedback taken from users who have been recommended items. We have developed the prototype for the proposed architecture and preliminary evaluation has been done. © Research India Publications.
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K. V. Kumar, Reddy, R. R., Balasubramanian, R., Sridhar, M., Sridharan, K., and Dr. Venkataraman D., “Automated recommendation system with feedback analysis”, International Journal of Applied Engineering Research, vol. 10, pp. 22201-22210, 2015.