Authors:
Omaia Mohammad Al-Omari,Nazlia Omar,DOI NO:
https://doi.org/10.26782/jmcms.2020.03.00021Keywords:
BOW extraction,Document classification,NV extraction,KNN classifier,NB classifier,SVM classifier,Abstract
There has been a significant growth in the digital word as per the documents are concerned. The classification of digital document is a big trend in the market as a revolution. However the classification of the document is a big task for the modern applications. There are various terms that are used for the extraction of information from the documents. The main concerned areas for the document classification are the noun and the verbs that broadly signify the topics and events. The use of NV (Noun Verb) techniques is a common and powerful practice for the words to be classified. The performance of the document depends on the NV technique due to the classification of the document. The main aim of the work shown in this study is to enhance the capability of the NV extraction methodology to classify the documents. Three classifiers namely, K-Nearest Neighbor (KNN), Naive Bayes (NB), and Support Vector Machine (SVM) are used for the comparison of the results. Various benchmark set are used in this study for the evaluation of the accuracy of the data sets. The data sets were taken from Reuters 8 and WebKb for this purpose. Other extraction methods were also enhanced and incorporated with the NV method extraction e.g., Nouns, Bag of Word (BOW), and Verbs. The results are studied and the conclusion follows themRefference:
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