Recommendation System: Techniques, Evaluation and Limitations
Shruthi N1, Sunitha R S2, Lincy Mathews3
1Shruthi N, Pursuing M. Tech in IS&E Department of RIT
2Sunitha R., Assistant Professor in IS&E Department of RIT.
3Lincy Mathews, Assistant Professor in IS&E Department of RIT.
Manuscript received on July 20, 2019. | Revised Manuscript received on August 10, 2019. | Manuscript published on August 30, 2019. | PP: 2097-2101 | Volume-8 Issue-6, August 2019. | Retrieval Number: F8479088619/2019©BEIESP | DOI: 10.35940/ijeat.F8479.088619
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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: For the benefits of the user in selecting items based on their interests, the recommendation technology is developed in different domains. A recommender system is one of the major techniques, that handles information overload problem of Information Retrieval by suggesting users with appropriate and relevant items. This paper surveys recommendation technology, the challenges and its solutions. Recommendation technology is applied in many areas like movies, videos, books, research papers, libraries, music, news, tourism, etc. This survey is useful for the further implementation and analysis of how users are adapting these technologies and how helpful it is for the user. This work also helps understand the different techniques of recommendation systems and how they can be evaluated.
Keywords: Collaborative filtering, Content-based filtering, Context-based filtering, Hybrid approach, Recommendation system.