The Recommender Systems Model for Smart Cities
Sandeep Tayal1, Kapil Sharma2
1Sandeep Tayal, Assistant Professor, Department of Computer Science and Engineering, Maharaja Agrasen Institute of Technology and Delhi Technological University, (Delhi), India.
2Kapil Sharma, Professor and Head, Department of Information Technology, Delhi Technological University, (Delhi), India.
Manuscript received on 05 August 2019 | Revised Manuscript received on 28 August 2019 | Manuscript Published on 05 September 2019 | PP: 451-456 | Volume-8 Issue-2S7 July 2019 | Retrieval Number: B10830782S719/2019©BEIESP | DOI: 10.35940/ijrte.B1083.0782S719
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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: Recommender systems were introduced in the early 1990s. They did not get too much attention and were limited to a narrow domain implemented by only a few companies until the outburst of E-commerce. As online shopping became popular, the recommender system started becoming an integral part of an organization marketing strategy and since then they have completely evolved a lot. This give an opportunity to start with a recommendation System project by collecting information from news of users to provide a best recommendation. The cities become smatter so, this paper review different methods of implementing Recommender systems models for smart cities along with their drawbacks and possible improvements.
Keywords: Content-Based System, Collaborative Filtering, Evaluation, Hybrid System, Recommender System, Smart Cities.
Scope of the Article: IoT Applications for Smart Cities