Recommendation System: Techniques and Issues
Sushma Malik1, Mamta Bansal2
1Sushma Malik, Research Scholar, Shobhit Deemed University, Meerut.
2Dr. Mamta Bansal, Professor, School of Engg. & Tech. Dept. of CSE, Shobhit Deemed University, Meerut.
Manuscript received on 5 August 2019. | Revised Manuscript received on 11 August 2019. | Manuscript published on 30 September 2019. | PP: 2821-2824 | Volume-8 Issue-3 September 2019 | Retrieval Number: C5211098319/2019©BEIESP | DOI: 10.35940/ijrte.C5211.098319
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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: In daily life user searched the many things over the internet on the basis of requirement with the help of search engines. Recommendation systems are widely used on the internet to help the user in discover the products or services that are best with their individual interest. RS effectively reduce the information overload by providing personalized suggestions to user when searching for items like movies, songs, or books etc. The main aim of RS is to help the users by providing the surface of information that relevant to them, fulfill their needs and their task. The paper provides an overview of RS and analyze the different approaches used for develop RS that include collaborative filtering, content-based filtering and hybrid approach of recommender system.
Keywords: Recommender System (RS), Content Based (CB), Collaborative Filtering (CF), Cold Start Problem, Shilling Attack
Scope of the Article: Computational Techniques in Civil Engineering