Shahnewaz Ul Islam Chowdhury

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We want to predict the next song a user might prefer to listen based on their previous listening patterns, currently played songs and similar music based on music data. To calculate music similarity we used a Matlab toolbox that considers audio signals. We used association rule mining to find users' listening patterns and using the association rules we(More)
In this paper, we are proposing a personalized music recommender service based on Mamdani Fuzzy Interference System (M-FIS). Collection of playlist is used for gathering users' choice and mood while listening to songs. Similarity between audio files is calculated based on Mel Frequency Cepstral Coefficients (MFCC). We have developed a recommender model(More)
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