Comparison Between Bag of Words and Word Sense Disambiguation

DOI

10.2991/icacsei.2013.103How to use a DOI?

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ayoub Mohamed H. Elyasir
AU  - Kalaiarasi Sonai Muthu Anbananthen
PY  - 2013/08
DA  - 2013/08
TI  - Comparison Between Bag of Words and Word Sense Disambiguation
BT  - Proceedings of the 2013 International Conference on Advanced Computer Science and Electronics Information (ICACSEI 2013)
PB  - Atlantis Press
SP  - 413
EP  - 417
SN  - 1951-6851
UR  - https://doi.org/10.2991/icacsei.2013.103
DO  - 10.2991/icacsei.2013.103
ID  - MohamedH.Elyasir2013/08
ER  -