MF-NB learning based approach for recommendation system
Автор: Hutashan V. Bhagat, Shashi B., Sachin M.
Журнал: International Journal of Information Technology and Computer Science @ijitcs
Статья в выпуске: 10 Vol. 10, 2018 года.
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The Multi Factor-Naive Bayes classifier based recommendation system is analyzed with respect to the traditional KNN classifier based recommendation system. The classification of the web usage data is done on the basis of the keyword name, keyword count, inbound links and age group of the users. Whereas, in traditional KNN the URL was the only factor that was considered for the purpose of classification. The performance evaluation is done in the terms of RMSE, Error Rate, Accuracy Rate and Precision. The MF-NB is observed to be outperforming the KNN classifier in all respective terms.
Data Mining, Web Usage Data Mining, Classification, Naïve Bayes Classification, KNN Classifier
Короткий адрес: https://sciup.org/15016304
IDR: 15016304 | DOI: 10.5815/ijitcs.2018.10.04
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