Recommendation Systems in the Big Data Era
Neelam Singh1, Shivanshi Tripathi2, Devesh Pratap Singh3, Bhasker Pant4, Vijay Kumar5
1Neelam Singh, Department of Computer Science and Engineering, Graphic Era deemed to be University, Dehradun (Uttarakhand), India.
2Shivanshi Tripathi, Department of Computer Application, Graphic Era deemed to be University, Dehradun (Uttarakhand), India.
3Devesh Pratap Singh, Department of Computer Science and Engineering, Graphic Era deemed to be University, Dehradun (Uttarakhand), India.
4Bhasker Pant, Department of Computer Science and Engineering, Graphic Era deemed to be University, Dehradun (Uttarakhand), India.
5Vijay Kumar, Department of Physics, Graphic Era Hill University, Dehradun (Uttarakhand), India.
Manuscript received on 16 June 2020 | Revised Manuscript received on 27 June 2020 | Manuscript Published on 04 July 2020 | PP: 80-85 | Volume-8 Issue-12S3 October 2019 | Retrieval Number: L100610812S319/2020©BEIESP | DOI: 10.35940/ijitee.L1006.10812S319
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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: Rapid progression in technology and increasing use of social media platforms like Facebook, Instagram and Twitter has altered the way of articulating people’s judgment, observation and sentiments about specific product, services, and more. This leads to the production and accumulation of massive amount of data. Recommendation systems are getting impetus when it comes to find insights from this data to make decisions that can be represented in various statistical and graphical forms. They have proven useful in predicting or recommending products ranging from food, movies, restaurants etc. This paper presents an overview about recommendation systems and a review of generation of recommendation methods based on categories like content-based, collaborative, and hybrid approaches. The paper will enlist the limitations which the present recommendation system faces and the possible improvements required in their capabilities to fit into a wider range of application areas.
Keywords: Recommender System, Recommendation, Models, Data Analytics.
Scope of the Article: Big Data Security