DocumentCode :
2556829
Title :
Personalized recommendation engine using HADOOP
Author :
Sahu, Uma ; Tripathy, Amiya Kumar ; Chitnis, Apurva ; Corda, Karen Aubrey ; Rodrigues, Sharon
Author_Institution :
Dept. of Comput. Eng., Don Bosco Inst. of Technol., Mumbai, India
fYear :
2015
fDate :
4-6 Feb. 2015
Firstpage :
1
Lastpage :
6
Abstract :
More and more E-commerce Websites provide products with different prices which made it hard for consumers to find the products and services they want. In order to overcome this data overload, personalized recommendation engines are used to suggest products and to provide consumers with relevant data to help them decide which products to purchase. Recommendation engines are highly computational and hence ideal for the Hadoop Platform. This system aims at building a book recommendation engine which uses item or user based recommendation from Mahout for recommending books. It will analyze the data and give suggestions based on what similar users did and on the past transaction history of the user.
Keywords :
Web sites; electronic commerce; parallel processing; recommender systems; Hadoop platform; book recommendation engine; e-commerce Web sites; electronic commerce; personalized recommendation engine; Collaboration; Databases; Engines; Filtering; Java; Software; Sustainable development; HDFS; Hadoop; Mahout; Map Reduce; Personalization; Recommendation; Websites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technologies for Sustainable Development (ICTSD), 2015 International Conference on
Conference_Location :
Mumbai
Type :
conf
DOI :
10.1109/ICTSD.2015.7095901
Filename :
7095901
Link To Document :
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