International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015


A Survey on Feature Based Product Recommendation System

Akshay Giri | K. N. Honwadkar [5]


Abstract: The Recommender system is an essential part of the data and the e-commerce system. The system provides a highly powerful method for allowing users to filter out large set of information and the product places. The researchers from the same field are still working on how the recommender methodology is implemented in a particular domain. The software product engineering uses Feature Models (FMs) technology in a broad manner for helping and validating each product structure and it also provides support for the domain analysis. The creation of FM is tedious and very time-requiring technology. Now a day, its popular to buy a product online and online product shopping is a new trade in E-Commerce domain. The customers can choose their preferred products and buy many products online from the Online shopping website or portal. Online shopping websites combine Business-to-Consumers, Business-to-business as well as Consumers-to-Consumers services with each other. Because of the customized, high feature and cost capability products the universality of the software is increases. Model-Driven Software Product Lines (MDSPL) permits the creators to construct a product based on the configuration information and the reusable resources automatically. A product line is constructed from a public set of resources.


Keywords: Model-Driven software product lines, Feature models, E-commerce, Business-to-Business, Business-to-Consumers and Consumers-to-Consumers, Domain Engineering, Application Engineering


Edition: Volume 4 Issue 1, January 2015,


Pages: 139 - 142


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How to Cite this Article?

Akshay Giri, K. N. Honwadkar, "A Survey on Feature Based Product Recommendation System", International Journal of Science and Research (IJSR), Volume 4 Issue 1, January 2015, pp. 139-142, https://www.ijsr.net/get_abstract.php?paper_id=SUB1583

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