COLLABORATIVE FILTERING BASED TOP-N RANKED RECOMMENDER SYSTEM: AN IMPLEMENTATION AND COMPARISON METHODOLOGY
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Keywords
Top-n Ranked Recommendation, Collaborative Filtering, Recommender System Techniques, Comparative analysis.
Abstract
The trend of digital explorations especially on e-Commerce websites is being witnessed with the fast-growing use of the internet. It led commercials to understand their consumers' behaviour more accordingly. In this paper, we implemented an Artificial Intelligence based technique called Collaborative Filtering on the dataset we created to obtain top-n ranked recommendations for the books on Artificial Intelligence (AI). We also compared our work with other similar implementation of AI based recommender systems to show the differences in the methodologies and approaches that are published by other users.
References
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Sajid Ansari
Department of Computer Science and Engineering, Jamia Hamdard, New Delhi
Md. Imran
Department of Computer Science and Engineering, Jamia Hamdard, New Delhi
Piyush Kumar Gupta
Department of Computer Science and Engineering, Jamia Hamdard, New Delhi