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An Efficient Personalized POI Recommendation using PCA-SVM based Filtering and Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 7 |
| Year of Publication: 2017 |
| Authors: Sunayna Sharma, Anil Suryavanshi |
10.5120/ijca2017915801
|
Sunayna Sharma, Anil Suryavanshi . An Efficient Personalized POI Recommendation using PCA-SVM based Filtering and Classification. International Journal of Computer Applications. 177, 7 ( Nov 2017), 23-28. DOI=10.5120/ijca2017915801
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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