Location Recommendation System on Point of Interest and Place-User Similarity
Deepika P1, R.Parvathi2

1Deepika P, M Tech CSE-BD, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai India.
2R.Parvathi, Associate Professor, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai India.

Manuscript received on April 02, 2020. | Revised Manuscript received on April 21, 2020. | Manuscript published on May 30, 2020. | PP: 1092-1094 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2257059120/2020©BEIESP | DOI: 10.35940/ijrte.A2257.059120
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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: Social Networking media and Internet handles ample ranging of the datasets and that can be synthesised and casted up to demonstrate the patterns ,drifts and association related to the nature of the individual and intercommunications. The rapid development of the networking connections made it further intricated to gain the required facts and figures from the voluminous data. The recommendation systems are the gadgets that proposes the users help with their requirements. Various filtering methods are available with which blend of two or more such methods provide hybrid variety of recommendation. This paper proposes a personalized location based recommendation based on two models i.e. point of interest and place-user similarity model respectively to produce more accurate recommendations. The developed models are evaluated with precision and recall measures. 
Keywords: Social Networks, Intercommunication, Large Datasets, filtering methods, personalized location recommendation, point of interest, place-user similarity, precision, recall.
Scope of the Article: GPS and Location-Based Applications