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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Linguistics Society of Iran</PublisherName>
				<JournalTitle>Language and Linguistics</JournalTitle>
				<Issn>23223847</Issn>
				<Volume>5</Volume>
				<Issue>10</Issue>
				<PubDate PubStatus="epublish">
					<Year>2009</Year>
					<Month>11</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Review of Lexicon in MT Systems</ArticleTitle>
<VernacularTitle>A Review of Lexicon in MT Systems</VernacularTitle>
			<FirstPage>135</FirstPage>
			<LastPage>150</LastPage>
			<ELocationID EIdType="pii">1560</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Arezoo</FirstName>
					<LastName>Molavi Vardanjani</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2009</Year>
					<Month>12</Month>
					<Day>05</Day>
				</PubDate>
			</History>
		    <Abstract>Understanding how human mind access mental lexicon, and being aware of knowledge representation mechanism, would help us a great deal to design natural language processing systems. This research seeks to investigate the lexicon in machine translation (MT) systems, and then to propose a representation system for its lexicon using concepts and relation links between them, which can be utilized to enhance the efficiency of MT systems. Finally, the performance of this mechanism is illustrated through conceptual graphs.</Abstract>
			<OtherAbstract Language="FA">Understanding how human mind access mental lexicon, and being aware of knowledge representation mechanism, would help us a great deal to design natural language processing systems. This research seeks to investigate the lexicon in machine translation (MT) systems, and then to propose a representation system for its lexicon using concepts and relation links between them, which can be utilized to enhance the efficiency of MT systems. Finally, the performance of this mechanism is illustrated through conceptual graphs.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">MT system</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">natural language processing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">conceptual representation of lexicon</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://lsi-linguistics.ihcs.ac.ir/article_1560_3a20f62a0af1aa152670bab3c602feed.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
