A Firefly Approach to Collaborative Filtering based Recommender Systems through Fuzzy Features
Krishan Kant Yadav1, Venkatadri Marriboyina2, Sanjiv Sharma3

1Krishan Kant Yadav, Research Scholar, Department of Computer Science & Engineering, Amity University, Gwalior (Madhya Pradesh), India.
2Dr. Venkatadri Marriboyina, Professor, Department of Computer Science & Engineering, Amity University, Gwalior (Madhya Pradesh), India.
3Dr. Sanjiv
Sharma, Professor, Department of CS & IT, Madhav Institute of Technology & Science, Gwalior (Madhya Pradesh), India.

Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1510-1514 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6323058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Recommender system (RS) is most important methods which offer the recommendation to the online user with ease to make his right decisions on items or services. The User-based Collaborative Filtering (CF) technique is one of mainly important method amongst various recommender systems.Collaborative Filtering (CF) approaches are either model-based/ memory-based. While the previous is more precise, it’s not flexible in compare of model-based approach. Here we proposed a hybrid fuzzy-firefly method to RS, which maintain the precision of memory considered as CF & scalability of model considered as CF. Utilizing the hybrid characteristics, new user model (UM) has been created, which assisted in reaching vital reduction in system difficulty, sparse & create the grip of neighbour transitivity association. UM is working to discovery group of compatible clients in which a memory-based hunt is performed. Experimental results on Movie Lens dataset shows that proposed method not only improves recommendation accuracy significantly but also increases quality of prediction and recommendation performance.
Keyword: Collaborative Filtering; Fuzzy Logic; Firefly Algorithm; Recommender Systems.
Scope of the Article: Systems and Software Engineering.