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Volume & Issue no: Volume 3, Issue 6, November - December 2014

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Title:
RECOMMENDATION WITH DATA MINING ALGORITHMS FOR E-COMMERCE AND M-COMMERCE APPLICATIONS
Author Name:
Ashfaq Amir Shaikh, Dr. Gulabchand K. Gupta
Abstract:
Abstract Recommendation is widely used technique to guide user to choose the right product online as it becomes the essential feature for the successful E-commerce or M-commerce application, as information grows exponentially over the time on the internet the accurate recommendation with less processing time is the greater challenge, several approach is proposed about recommendation like collaborative filtering and others, but is causes the scalability and processing problem as information grows, the proposed system is simple user rating based simple product analysis and gives better recommendation about any product using some data mining approach like classification, clustering, association and other Technique. The Java EE based web application as Java Server Pages (JSP) is user as View to accept the parameter from user, the database maintains with Hibernate Technology as a Model and application support Model View Design Pattern, also data mining analysis done using WEKA Data Mining tool and based on the user parameter like product name, brand, price range and specific features or specifications the system will all sort of analysis using exiting user rating, feedback and other processing the final result will be generated as recommendation product. The Mobile based user interface is also given like Java Based Mobile Application using J2ME and Android User Interface using Android API. Keywords:-E-commerce, M-commerce, Jave EE, Java Server
Cite this article:
Ashfaq Amir Shaikh, Dr. Gulabchand K. Gupta , " RECOMMENDATION WITH DATA MINING ALGORITHMS FOR E-COMMERCE AND M-COMMERCE APPLICATIONS " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 6, November - December 2014 , pp. 115-118 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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