Abstract:
"
In the last couple of decades, there has been a rapid increase in the use of
recommendation systems. Even though there has been many approaches proposed
from various studies, there is a very less amount of researches has addressed the
common recommendation problems such as cold- start problem, over specialization
and accuracy issues. This research is carried out on proposing a hybrid approach using
traditional methods as well as machine learning to address all those above-mentioned
problems at once and optimize the effectiveness of recommendation systems."
