Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)

Comparison Between Bag of Words and Word Sense Disambiguation

Authors
Ayoub Mohamed H. Elyasir, Kalaiarasi Sonai Muthu Anbananthen
Corresponding author
Mohamed H. Elyasir
Keywords
Data Mining, Bag of Words, Word Sense Disambiguation, Classifier
Abstract
Bag of Words (BoW) and Word Sense Disambiguation (WSD) are the main approaches utilized in almost every data mining project for classification and data processing. The two approaches are extensively used in constructing various classifiers including supervised, unsupervised and semi-supervised classifiers. In this paper, we introduce new method of defining and comparing between BoW and WSD based on three categories. First, introduce and explain the approaches through the human brain analogy to simplify the overall concept. Secondly, sort their classifiers, methodologies and algorithms in the data mining field. Finally, introduce our developed cognitive miner to illustrate the practical functionality of these two approaches.
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