Title :
Personalised book recommendation system based on opinion mining technique
Author :
Kumari Priyanka;Anand Shanker Tewari;Asim Gopal Barman
Author_Institution :
CSE department, NIT Patna, Patna, India
fDate :
4/1/2015 12:00:00 AM
Abstract :
Recommendation systems are tools in e-commerce websites which helps user to find the most suitable products. From the huge number of books, it is really difficult to choose a particular book. So, the recommendation system technique plays very important role and helps user to get books according to their need and interest. This paper presents online book recommendation system for users who purchase books by considering specific features of a book. These features include language, publisher, author, content, price, edition etc. The main motive of this paper is to develop a technique which recommends the most suitable books to users according to the specific features of the book that are of their own interest. In this paper we have used the features of a product, extracted from the reviews for recommendation. This is based on the combined features of classification and opinion mining technique.
Keywords :
"Feature extraction","Web sites","Classification algorithms","Business","Sentiment analysis","Text categorization"
Conference_Titel :
Communication Technologies (GCCT), 2015 Global Conference on
DOI :
10.1109/GCCT.2015.7342668