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Title: Semantic similarity measures for information retrieval systems using ontology
Researcher: Saruladha, K
Guide(s): Aghila, G
Keywords: Ontology
New Information Content (NIC) Measure
Computer Science
Tversky Psychological Model
Upload Date: 22-Nov-2012
University: Pondicherry University
Completed Date: September, 2011
Abstract: This work focuses on devising computational models for assessing similarity among words/concepts in the knowledge sources like ontologies. Semantic similarity assessment plays an important role in the fields of Psychology, Information Retrieval and Information Integration systems. The paradigm shift of syntactic web to semantic web has emphasized the use of development of semantic similarity measures to computationally identify related concepts within and among ontologies. This work deals with semantic similarity approaches which exploit the concept relationships associated with the concepts to quantify similarity among concepts defined within and among ontologies. The work specifically is interested in proposing corpus independent information content based measures for quantifying similarity among concepts belonging to single and multiple knowledge sources. The information content computation of these measures has been redefined with taxonomic and non taxonomic relations possessed by the concepts defined in the ontology. This new definition of information content solves the sparse data problem prevalent in corpus. It adds a new dimension to existing definition of information content as it is defined independent of the corpus statistics. Apart from this it also defines a generalized way of quantifying information content of the concepts, which enables to capture the semantics of the concept. Accordingly, the New Information Content (NIC) based similarity measures NICResnik, NICLin and NICJandC were defined and used to measure the similarity among concepts belonging to the lexical ontology WordNet. The effectiveness of the proposed similarity measures was evaluated using the Psycholinguistic approach. The literature on information retrieval system reveals that similarity measures play a major role in computing document and query similarity. In general, the keywords of the documents are used in the indexing process to retrieve the documents.
Pagination: xx, 185p.
Appears in Departments:Department of Computer Science

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01_title.pdfAttached File82.09 kBAdobe PDFView/Open
02_certificate.pdf79.77 kBAdobe PDFView/Open
03_declaration.pdf40.65 kBAdobe PDFView/Open
04_acknowledgement.pdf89.78 kBAdobe PDFView/Open
05_abstract.pdf92.02 kBAdobe PDFView/Open
06_content.pdf142.57 kBAdobe PDFView/Open
07_list of tables.pdf112.09 kBAdobe PDFView/Open
08_list of figures.pdf114.07 kBAdobe PDFView/Open
09_chapter 1.pdf294.18 kBAdobe PDFView/Open
10_chapter 2.pdf1.13 MBAdobe PDFView/Open
11_chapter 3.pdf1.01 MBAdobe PDFView/Open
12_chapter 4.pdf1.21 MBAdobe PDFView/Open
13_chapter 5.pdf586.16 kBAdobe PDFView/Open
14_chapter 6.pdf146.71 kBAdobe PDFView/Open
15_references.pdf177.13 kBAdobe PDFView/Open
16_list of publications.pdf140.97 kBAdobe PDFView/Open
17_vitae.pdf83.01 kBAdobe PDFView/Open
18_appendix.pdf104.25 kBAdobe PDFView/Open

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