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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Isfahan University of Medical Sciences</PublisherName>
				<JournalTitle>Health Information Management</JournalTitle>
				<Issn>1735-7853</Issn>
				<Volume>7</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2010</Year>
					<Month>06</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Document-Term Clustering: Proximity of Subjects Correspond with Psychology of Marriage in Biomedicine Literature during the Years “1990-99” and “2000-2008”</ArticleTitle>
<VernacularTitle>Document-Term Clustering: Proximity of Subjects Correspond with Psychology of Marriage in Biomedicine Literature during the Years “1990-99” and “2000-2008”</VernacularTitle>
			<FirstPage></FirstPage>
			<LastPage></LastPage>
			<ELocationID EIdType="pii">10983</ELocationID>
			
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad</FirstName>
					<LastName>Tavakolizadeh Ravari</LastName>
<Affiliation>Assistant Professor, Library and Information Science, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Maryam</FirstName>
					<LastName>Nejabatian</LastName>
<Affiliation>Msc, Psychology, National Youth Organization, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2011</Year>
					<Month>03</Month>
					<Day>07</Day>
				</PubDate>
			</History>
		<Abstract>Introduction: The study on psychology of marriage rooted in the social issues. The field has also found its way to biomedicine. The current research, based on the document-term clustering methods, focus on term-proximity of documents that were related to the field of psychology of marriage in biomedicine literature.Methods: The co-occurrence frequency of terms within the two different corpuses of documents resulted in two proximity matrixes. The corpuses contained sequentially the documents published during the years “1990-99” and 2000-2008”. Those documents were returned by two separate searches in Medline. The cosine method was established to determine the proximity of terms. Besides, the terms were clustered by the Ward’s method.Results: The measurement of term-proximity resulted in two graphs of hierarchical clusters. The comparison revealed that twenty terms up to thirty-eight kept permanently their proximity with one or more other terms during the two periods of study adult and 21(60%) prenatal had a correct sequence.Conclusion: Dividing correspond subjects with psychology of marriage into five areas prepares the opportunity to compare the two hierarchical graphs and find the relationship between and within those areas. Consequently, document-term clustering assists to answer some reference queries.Keywords: Psychology; Marriage; Classifications; Medicine in Literature; Medline; Subject Headings.</Abstract>
			<OtherAbstract Language="FA">Introduction: The study on psychology of marriage rooted in the social issues. The field has also found its way to biomedicine. The current research, based on the document-term clustering methods, focus on term-proximity of documents that were related to the field of psychology of marriage in biomedicine literature.Methods: The co-occurrence frequency of terms within the two different corpuses of documents resulted in two proximity matrixes. The corpuses contained sequentially the documents published during the years “1990-99” and 2000-2008”. Those documents were returned by two separate searches in Medline. The cosine method was established to determine the proximity of terms. Besides, the terms were clustered by the Ward’s method.Results: The measurement of term-proximity resulted in two graphs of hierarchical clusters. The comparison revealed that twenty terms up to thirty-eight kept permanently their proximity with one or more other terms during the two periods of study adult and 21(60%) prenatal had a correct sequence.Conclusion: Dividing correspond subjects with psychology of marriage into five areas prepares the opportunity to compare the two hierarchical graphs and find the relationship between and within those areas. Consequently, document-term clustering assists to answer some reference queries.Keywords: Psychology; Marriage; Classifications; Medicine in Literature; Medline; Subject Headings.</OtherAbstract>
<ArchiveCopySource DocType="pdf">https://him.mui.ac.ir/article_10983_76b605730bd2606bbcb290f1244dac9a.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
