Ontology and context based recommendation system using Neuro-Fuzzy Classification

2019 ◽  
Vol 74 ◽  
pp. 498-510 ◽  
Author(s):  
A. Razia Sulthana ◽  
Subburaj Ramasamy
Keyword(s):  
Recommendation System ◽  
Fuzzy Classification ◽  
Neuro Fuzzy

Movie Recommendation System Based on Fuzzy Inference System and Adaptive Neuro Fuzzy Inference System

Fuzzy Systems ◽  
2017 ◽  
pp. 573-608
Author(s):  
Mahfuzur Rahman Siddiquee ◽  
Naimul Haider ◽  
Rashedur M. Rahman
Keyword(s):  
Fuzzy Inference System ◽  
Recommendation System ◽  
Fuzzy Inference ◽  
Pearson Correlation ◽  
Similarity Measures ◽  
Manhattan Distance ◽  
Comparative Performance ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Similarity Calculation

One of most prominent features that social networks or e-commerce sites now provide is recommendation of items. However, the recommendation task is challenging as high degree of accuracy is required. This paper analyzes the improvement in recommendation of movies using Fuzzy Inference System (FIS) and Adaptive Neuro Fuzzy Inference System (ANFIS). Two similarity measures have been used: one by taking account similar users' choice and the other by matching genres of similar movies rated by the user. For similarity calculation, four different techniques, namely Euclidean Distance, Manhattan Distance, Pearson Coefficient and Cosine Similarity are used. FIS and ANFIS system are used in decision making. The experiments have been carried out on Movie Lens dataset and a comparative performance analysis has been reported. Experimental results demonstrate that ANFIS outperforms FIS in most of the cases when Pearson Correlation metric is used for similarity calculation.

scholarly journals Text Extraction Using Component Analysis and Neuro-fuzzy Classification on Complex Backgrounds

2011 ◽  
pp. 742-751
Author(s):  
Michael Makridis ◽  
Nikolaos E. Mitrakis ◽  
Nikolaos Nikolaou ◽  
Nikolaos Papamarkos
Keyword(s):  
Component Analysis ◽  
Fuzzy Classification ◽  
Text Extraction ◽  
Neuro Fuzzy
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