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An Improved Approach for Word Ambiguity Removal
Priti R Saktel, Urmila Shrawankar
Pages - 71 - 82     |    Revised - 15-09-2012     |    Published - 25-10-2012
Volume - 3   Issue - 3    |    Publication Date - October 2012  Table of Contents
Human Computer Interaction, Supervised Training, Unsupervised Learning, Word Ambiguity, Word Sense Disambiguation
Word ambiguity removal is a task of removing ambiguity from a word, i.e. correct sense of word is identified from ambiguous sentences. This paper describes a model that uses Part of Speech tagger and three categories for word sense disambiguation (WSD). Human Computer Interaction is very needful to improve interactions between users and computers. For this, the Supervised and Unsupervised methods are combined. The WSD algorithm is used to find the efficient and accurate sense of a word based on domain information. The accuracy of this work is evaluated with the aim of finding best suitable domain of word. Keywords: Human Computer Interaction, Supervised Training, Unsupervised Learning, Word Ambiguity, Word sense disambiguation
CITED BY (1)  
1 Saktel, P., Domke, M., & Vilhekar, L. Performance Improvement of Context Identification for Human Computer Interaction.
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Miss Priti R Saktel
GHRCE - India
Dr. Urmila Shrawankar
G. H. Raisoni College of Engineering Nagpur, - India