Abstract

The rapid growth of cities has developed an increasing number of points of interest (POIs), e.g., restaurants, stores, hotels, etc; to enrich people’s life, providing us with more choices of life experiences than before. People are willing to explore the city and neighborhood in their daily life and decide “where they should go” according to their personal interest and various choices of POIs. The Existing Methodology implemented for the Filtering of POI Recommendation is efficient but contains less Precision and Recall, hence a new and efficient technique for the POI Recommendation using Principle Component Analysis with Support Vector Machine Learning is proposed which provides more efficient results in comparison.

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