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dc.contributor.advisorChairperson, Graduate Committee: Rafal A. Angryken
dc.contributor.authorMcAllister, Richard Arthuren
dc.date.accessioned2013-06-25T18:38:10Z
dc.date.available2013-06-25T18:38:10Z
dc.date.issued2009en
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/1813en
dc.description.abstractLanguage ontologies provide an avenue for automated lexical analysis that may be used in concert with existing information retrieval methods to allow lexicographic relationships to be considered in searches. This paper presents a method of information retrieval that uses WordNet, a database of lexical ontologies, to generate paths of abstraction via lexicographic relationships, and uses these relationships as the basis for an inverted index to be used in the retrieval of documents from an indexed corpus. We present this method as a entree to a line of research in using lexical ontologies to perform graph analysis of documents, and through this process improve the precision of existing information retrieval techniques.en
dc.language.isoenen
dc.publisherMontana State University - Bozeman, College of Engineeringen
dc.subject.lcshInformation retrievalen
dc.subject.lcshText processing (Computer science)en
dc.subject.lcshData miningen
dc.subject.lcshComputer programsen
dc.titleFP-Tree motivated system for information retrieval using an abstraction path-based inverted indexen
dc.typeThesisen
dc.rights.holderCopyright 2009 by Richard Arthur McAllisteren
thesis.catalog.ckey1538667en
thesis.degree.committeemembersMembers, Graduate Committee: John Sheppard; Denbigh Starkey; Stephen Durbinen
thesis.degree.departmentComputer Science.en
thesis.degree.genreThesisen
thesis.degree.nameMSen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage92en


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