A Concise Analysis of Various Recommendation Methods and Techniques for Efficient Recommender Systems

Authors

  • R Akil Sindhu Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi, India
  • R Manicka Chezian Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi, India

Keywords:

Recommendation Algorithm, Content Based Filtering, Collaborative Filtering, Hybrid Recommendation, Knowledge Based Recommendation, Data Mining Methods

Abstract

Recommender Systems are eminently in demand to manage the problem of highly overloading data and to avoid the retrieval of irrelevant information from Web, which is a major part of Information Filtering. Recommender Systems helps user to make precise and explicit decisions and study the user’s knowledge to enhance the Business growth. Different Recommendation methods are implemented for achieving varied recommendations in numerous vital applications based on the expected behavior of the system and relevant data mining strategies are used to perform efficient information retrieval. This paper analyses the various Recommendation methods available for building effective Recommender Systems and exploits the participation and usage of Recommendation methods in different domains. This paper also focuses to discuss Data Mining techniques and their scope towards implementing such effective Recommender Systems.

References

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Published

2025-11-11

How to Cite

[1]
R. Akil Sindhu and R. Manicka Chezian, “A Concise Analysis of Various Recommendation Methods and Techniques for Efficient Recommender Systems”, Int. J. Comp. Sci. Eng., vol. 4, no. 10, pp. 52–58, Nov. 2025.

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Section

Research Article