Association Rule Based Product Recommendation Using Big Data
| dc.contributor.author | Pavithra, K | |
| dc.contributor.author | Sumanth, Reddy M | |
| dc.date.accessioned | 2017-08-18T09:56:17Z | |
| dc.date.available | 2017-08-18T09:56:17Z | |
| dc.date.issued | 2017-08-18T09:56:17Z | |
| dc.description.abstract | Recommender systems are integral part of any ecommerce store in order to sustain and compete with other growing businesses. There are various recommendation techniques which are used to appropriately recommend a product to the active user. The recommendation techniques like content-based recommendation system, collaborative recommendation system, context aware recommendation system, knowledge based recommendation have their own limitations which could be overcome by using hybrid systems. Also, these existing systems alone are enough to recommend products by analysing huge amount of data in the databases of the respective large retailer stores. The recommendation system has to analyse large amount of data to provide better recommendation and such important issue can be addressed using Hadoop ecosystem. In this paper, a recommendation system for product based on Hadoop framework is proposed. The proposed system recommend products to the user depending on the products present in the user cart. First, it uses framework to import the product transactions. Furthermore, the Apriori for finding frequent itemsets and Association rules are implemented in Hadoop and processing the data using MapReduce. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/8509 | |
| dc.language.iso | en | en_US |
| dc.subject | Sumanth Reddy M | en_US |
| dc.subject | Association Rule Based Product Recommendation Using Big Data | en_US |
| dc.subject | 1Nh13IS076 | en_US |
| dc.title | Association Rule Based Product Recommendation Using Big Data | en_US |
| dc.type | Other | en_US |