International Journal of Scientific Review and Research in Engineering and Technology

ISSN NUMBER:2455-3603 [ONLINE]
DIGITAL PUBLICATION IDENTIFIER: 16.10069.IJSRRET 
FOR DPI CONTACT  : IARC Research & Development, 77(II/A), Water Street, 8th Floor, New York, NY, 10005, United State
ARTICLE IS INVITED FOR VOLUME 3 ISSUE 3 - LAST DATE OF SUBMISSION:10/06/2018
ACCEPTANCE NOTIFICATION:WITHIN 7 DAYS - PUBLICATION DATE:15/06/2018

Current Issue

vol(1), Issue(6)
Title A SURVEY ON ONLINE SHOPPING RECOMMENDATION SYSTEM BASED ON VARIOUS CLASSIFICATION ALGORITHMS
Author Name Vishal A. Kanjariya*, Mosin Hasan
Institute Name Computer Engineering Department, BVM, V.V Nagar, Gujarat, India
Abstract Data mining is the key field which is used in the database management system. In the process of the data mining the relationships has been extracted between different attributes or features available in the product dataset. This paper provides a survey of shopping recommendation system and analyzes various Classification Algorithms which is helpful for Customer On-line Shopping Prediction. Customer based recommendation play an essential role in many data mining tasks that try to find interesting patterns from databases, such as association rules, sequences, classifiers, clusters and, many more of which the mining of association rules is one of the most popular techniques. Also in this paper different algorithms have been described used for product data mining procedure. In the processing of classification different classifier based on rules, distances have been utilized and more. Thus algorithms brief information has been provided in this paper. This paper contains information about dataset attributes or key-featureswhich is already available in onlineshopping dataset. In this paper data classification approaches has been described that can be utilized for dataset classification.
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