Mody University International Journal of Computing and Engineering Research

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Efficiency Booster Techniques for Recommendation System


Affiliations
1 Dept. of Computer Science, Mody University of Science and Technology, Sikar, Rajasthan, India
2 Dean, School of Engineering and Technology, Mody University of Science and Technology, Sikar, Rajasthan, India
 

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Recommendation Systems (RS) work as guides, it is guiding users to find products of their interest. It’s a fact that with the increase in RS deployment, traditional methods need modifications. Many techniques and different approaches have been developed to generate an effective recommendation. This is interesting as different application’s scenarios could have a fittest solution. This article throws light on techniques to turn the traditional methods more useful for real-world scenario to boost the productivity of RS. Finally, proposed a similarity fusion method for increasing efficiency of a recommendation system.

Keywords

Algorithm, Efficiency, Recommender Systems, Similarities.
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  • Efficiency Booster Techniques for Recommendation System

Abstract Views: 273  |  PDF Views: 156

Authors

Neetu Singh
Dept. of Computer Science, Mody University of Science and Technology, Sikar, Rajasthan, India
V. K. Jain
Dean, School of Engineering and Technology, Mody University of Science and Technology, Sikar, Rajasthan, India

Abstract


Recommendation Systems (RS) work as guides, it is guiding users to find products of their interest. It’s a fact that with the increase in RS deployment, traditional methods need modifications. Many techniques and different approaches have been developed to generate an effective recommendation. This is interesting as different application’s scenarios could have a fittest solution. This article throws light on techniques to turn the traditional methods more useful for real-world scenario to boost the productivity of RS. Finally, proposed a similarity fusion method for increasing efficiency of a recommendation system.

Keywords


Algorithm, Efficiency, Recommender Systems, Similarities.

References