Stemming text-based web page classification using machine learning algorithms: a comparison
The research aim is to determine the effect of word-stemming in web pages classification using different machine learning classifiers, namely Naive Bayes (NB), k-Nearest Neighbour (k-NN), Support Vector Machine (SVM) and Multilayer Perceptron (MP). Each classifiers' performance is evaluated in...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science and Information Organization
2020
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/86791/1/AnsariRazali2020_StemmingTextBasedWebPageClassification.pdf http://eprints.utm.my/id/eprint/86791/ https://dx.doi.org/10.14569/ijacsa.2020.0110171 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |