Title: Target word selection in English to Persian translation using unsupervised approach

Authors: Mahmood Soltani; Heshaam Faili

Addresses: Natural Language and Text Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran ' Natural Language and Text Processing Laboratory, School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran

Abstract: This article studies different aspect of a new approach for resolving the problem of target word selection which can be used in machine translation systems. It uses a bilingual dictionary to find all possible translations of each word and then chooses the most appropriate alternative regarding the statistical information. A semantic dependency graph of different senses of word is generated and several ranking on nodes and edges of the graph are used to select the proper sense. Two different evaluation tasks named All-words and lexical-sample are run, which show the considerable improvements over other WSD methods on English to Persian translation system.

Keywords: WSD; word sense disambiguation; machine translation; mutual information; centrality algorithm; Persian language; target word selection; bilingual dictionary; semantic dependency; English to Persian translation.

DOI: 10.1504/IJAISC.2012.049003

International Journal of Artificial Intelligence and Soft Computing, 2012 Vol.3 No.2, pp.125 - 142

Received: 15 Jun 2010
Accepted: 14 May 2011

Published online: 29 Nov 2014 *

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