Amazon Product Co-Purchasing Network -Using Hadoop Framework
Leena Prajapati1, Shubhi Shrivastav2, Ruchi Agarwal3
1Leena Prajapati, Assistant System Engineer-Trainee TATA Consultancy Services Ltd.
2Shubhi Shrivastav, Associate Software Engineer, Birlasoft Ltd.
3Ruchi Agarwal, Associate Professor and HOD, Department of BCA, Birla Institute of Technology BIT, Mesra, Ranchi (Jharkhand), India.
Manuscript received on 16 November 2019 | Revised Manuscript received on 04 December 2019 | Manuscript Published on 10 December 2019 | PP: 153-156 | Volume-8 Issue-3S2 October 2019 | Retrieval Number: C10251083S219/2019©BEIESP | DOI: 10.35940/ijrte.C1025.1083S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: These days in advanced age, any online shop you visit uses type of recommendation system. The recommendation system basically is data filtering devices that make use of estimations and data to endorse the most huge things to a particular user. The recommendation system deals with the huge amount of data and hence there is a need of Hadoop platform to manage and process the data. In this paper, MapReduce algorithm is implemented to process the data which is present in the form of ID, title, ratings, categories, ASIN (Amazon Standard Identification Number) etc. and proposed a content based recommendation system using the Hadoop framework to recommend the similar items as per user’s liked and purchased items.
Keywords: Amazon Co-purchase Network, Map Reduce, Hadoop Framework, Recommendation System, Big Data Analysis.
Scope of the Article: Patterns and Frameworks