Building an Adaptive Recommendation Model Based on Fuzzy MP Neuron and Weighted Similarity Indicator

BAM BAHADUR SINHA ； DR. R. DHANALAKSHMI

《Journal of Information Science and Engineering》 37卷2期 (2021/03) Pp. 281-293

https://doi.org/10.6688/JISE.202103_37(2).0001

摘要

Recommender system is one of the most common data filtering techniques used. It helps to discover hidden patterns of information from a wide range of omnipresent products and services. When dataset drifts from scarcity to abundance, the most common methods such as collaborative filtering suffer from information sparsity complication, over-specification, and elevated computational complexity. We have created a hybrid model in this respect that considers between precision and computation time to produce the most appropriate products for customers in real time. We made use of imputation technique, fuzzy logic using novel similarity technique and McCulloch-Pitts (MP) Neuron to cope up with aforementioned complications. The experimental evaluation on MovieLens dataset and comparison with numerous state of art personalization models shows that the proposed model yields high efficiency and effectiveness. We tested the resultant classification accuracy of our proposed model using precision and recall.

關鍵字

recommendation ； fuzzy c-means ； MP neuron ； similarity ； precision ； recall