Examination of Location Based Services and User Preferences
C. Karpagam1, S. Gomathi2

1C. Karpagam, Department of Computer Science, Dr. N. G. P. Arts and Science College, Coimbatore (Tamil Nadu), India.

2Dr. S. Gomathi, Department of Computer Applications, Sri Ramakrishna College of Arts and Science, Coimbatore (Tamil Nadu), India.

Manuscript received on 24 November 2019 | Revised Manuscript received on 12 December 2019 | Manuscript Published on 30 December 2019 | PP: 342-346 | Volume-9 Issue-2S3 December 2019 | Retrieval Number: B10821292S319/2019©BEIESP | DOI: 10.35940/ijitee.B1082.1292S319

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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: Recent developments on mobile location information have driven efforts to mine user patterns of interest. Even start-up companies survey user interests to enrich their business. All medium and large organizations are paying attention to collect and store location data. With the support of unlimited computing power and memory of mobile phones we can apply proficient Deep Learning algorithms to determine an optimal solution for user interests. In this article, we aim to complete an overall survey on evolution of Location Based Services and the improvements in recent trends. We have categorized the evolution period in to three divisions covering from the year 2000 to till date.

Keywords: Challenges, Location based Services, Recent Trends, User Preferences.
Scope of the Article: Mobility and Location-Dependent Services