DocumentCode
3182324
Title
Unsupervised weighted graph for Word Sense Disambiguation
Author
Hessami, Ehsan ; Mahmoudi, Faribourz ; Jadidinejad, Amir Hossien
Author_Institution
Islamic Azad Univ., Qazvin, Iran
fYear
2011
fDate
11-14 Dec. 2011
Firstpage
733
Lastpage
737
Abstract
Word Sense Disambiguation is one of the essential tasks in the Natural Language Processing that it used to identify the correct sense of words. There are many approaches for Word Sense Disambiguation that in this paper proposes an algorithm based on weighted graph which has few parameters and does not require sense-annotated data for training. Also we used standard data sets to evaluate the algorithm.
Keywords
graph theory; natural language processing; natural language processing; unsupervised weighted graph; word sense disambiguation; Accuracy; Classification algorithms; Context; Dairy products; Educational institutions; Knowledge based systems; Semantics; tree; weighted graph; word sense disambiguation;
fLanguage
English
Publisher
ieee
Conference_Titel
Information and Communication Technologies (WICT), 2011 World Congress on
Conference_Location
Mumbai
Print_ISBN
978-1-4673-0127-5
Type
conf
DOI
10.1109/WICT.2011.6141337
Filename
6141337
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