Relationships between perceived features and similarity of images: A test of Tversky's contrast model.
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| Title: | Relationships between perceived features and similarity of images: A test of Tversky's contrast model. |
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| Authors: | Rorissa, Abebe1 arorissa@albany.edu |
| Source: | Journal of the American Society for Information Science & Technology. Aug2007, Vol. 58 Issue 10, p1401-1418. 18p. 29 Black and White Photographs, 3 Diagrams, 5 Charts. |
| Subjects: | Information storage & retrieval systems, Information retrieval, Information manipulation theory, Information theory, Mathematical models, Mathematical analysis, Axioms, Regression analysis, Information science |
| Abstract: | The rapid growth of the numbers of images and their users as a result of the reduction in cost and increase in efficiency of the creation, storage, manipulation, and transmission of images poses challenges to those who organize and provide access to images. One of these challenges is similarity matching, a key component of current content-based image retrieval systems. Similarity matching often is implemented through similarity measures based on geometric models of similarity whose metric axioms are not satisfied by human similarity judgment data. This study is significant in that it is among the first known to test Tversky's contrast model, which equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, in the context of image representation and retrieval. Data were collected from 150 participants who performed an image description and a similarity judgment task. Structural equation modeling, correlation, and regression analyses confirmed the relationships between perceived features and similarity of objects hypothesized by Tversky. The results hold implications for future research that will attempt to further test the contrast model and assist designers of image organization and retrieval systems by pointing toward alternative document representations and similarity measures that more closely match human similarity judgments. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of the American Society for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 25857870 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Relationships between perceived features and similarity of images: A test of Tversky's contrast model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Rorissa%2C+Abebe%22">Rorissa, Abebe</searchLink><relatesTo>1</relatesTo><i> arorissa@albany.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+the+American+Society+for+Information+Science+%26+Technology%22">Journal of the American Society for Information Science & Technology</searchLink>. Aug2007, Vol. 58 Issue 10, p1401-1418. 18p. 29 Black and White Photographs, 3 Diagrams, 5 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems%22">Information storage & retrieval systems</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Information+manipulation+theory%22">Information manipulation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Information+theory%22">Information theory</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Axioms%22">Axioms</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Information+science%22">Information science</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The rapid growth of the numbers of images and their users as a result of the reduction in cost and increase in efficiency of the creation, storage, manipulation, and transmission of images poses challenges to those who organize and provide access to images. One of these challenges is similarity matching, a key component of current content-based image retrieval systems. Similarity matching often is implemented through similarity measures based on geometric models of similarity whose metric axioms are not satisfied by human similarity judgment data. This study is significant in that it is among the first known to test Tversky's contrast model, which equates the degree of similarity of two stimuli to a linear combination of their common and distinctive features, in the context of image representation and retrieval. Data were collected from 150 participants who performed an image description and a similarity judgment task. Structural equation modeling, correlation, and regression analyses confirmed the relationships between perceived features and similarity of objects hypothesized by Tversky. The results hold implications for future research that will attempt to further test the contrast model and assist designers of image organization and retrieval systems by pointing toward alternative document representations and similarity measures that more closely match human similarity judgments. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of the American Society for Information Science & Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/asi.20606 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 1401 Subjects: – SubjectFull: Information storage & retrieval systems Type: general – SubjectFull: Information retrieval Type: general – SubjectFull: Information manipulation theory Type: general – SubjectFull: Information theory Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Mathematical analysis Type: general – SubjectFull: Axioms Type: general – SubjectFull: Regression analysis Type: general – SubjectFull: Information science Type: general Titles: – TitleFull: Relationships between perceived features and similarity of images: A test of Tversky's contrast model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Rorissa, Abebe IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2007 Type: published Y: 2007 Identifiers: – Type: issn-print Value: 15322882 Numbering: – Type: volume Value: 58 – Type: issue Value: 10 Titles: – TitleFull: Journal of the American Society for Information Science & Technology Type: main |
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