The Best of Both Worlds: Highlighting the Synergies of Combining Manual and Automatic Knowledge Organization Methods to Improve Information Search and Discovery.
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| Title: | The Best of Both Worlds: Highlighting the Synergies of Combining Manual and Automatic Knowledge Organization Methods to Improve Information Search and Discovery. |
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| Authors: | Cleverley, Paul H.1 p.h.cleverley@rgu.ac.uk, Burnett, Simon1 s.burnett@rgu.ac.uk |
| Source: | Knowledge Organization. 2015, Vol. 42 Issue 6, p428-444. 17p. 1 Color Photograph, 5 Diagrams, 2 Charts. |
| Subjects: | Computers, Computerized typesetting, Knowledge management, Computer science, Information storage & retrieval systems in the petroleum industry |
| Abstract: | Research suggests organizations across all sectors waste a significant amount of time looking for information and often fail to leverage the information they have. In response, many organizations have deployed some form of enterprise search to improve the "findability" of information. Debates persist as to whether thesauri and manual indexing or automated machine learning techniques should be used to enhance discovery of information. In addition, the extent to which a knowledge organization system (KOS) enhances discoveries or indeed blinds us to new ones remains a moot point. The oil and gas industry was used as a case study using a representative organization. Drawing on prior research, a theoretical model is presented which aims to overcome the shortcomings of each approach. This synergistic model could help to re-conceptualize the "manual" versus "automatic" debate in many enterprises, accommodating a broader range of information needs. This may enable enterprises to develop more effective information and knowledge management strategies and ease the tension between what are often perceived as mutually exclusive competing approaches. Certain aspects of the theoretical model may be transferable to other industries, which is an area for further research. [ABSTRACT FROM AUTHOR] |
| Copyright of Knowledge Organization is the property of IMR Press 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: 111161605 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: The Best of Both Worlds: Highlighting the Synergies of Combining Manual and Automatic Knowledge Organization Methods to Improve Information Search and Discovery. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cleverley%2C+Paul+H%2E%22">Cleverley, Paul H.</searchLink><relatesTo>1</relatesTo><i> p.h.cleverley@rgu.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Burnett%2C+Simon%22">Burnett, Simon</searchLink><relatesTo>1</relatesTo><i> s.burnett@rgu.ac.uk</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Knowledge+Organization%22">Knowledge Organization</searchLink>. 2015, Vol. 42 Issue 6, p428-444. 17p. 1 Color Photograph, 5 Diagrams, 2 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computers%22">Computers</searchLink><br /><searchLink fieldCode="DE" term="%22Computerized+typesetting%22">Computerized typesetting</searchLink><br /><searchLink fieldCode="DE" term="%22Knowledge+management%22">Knowledge management</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+science%22">Computer science</searchLink><br /><searchLink fieldCode="DE" term="%22Information+storage+%26+retrieval+systems+in+the+petroleum+industry%22">Information storage & retrieval systems in the petroleum industry</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Research suggests organizations across all sectors waste a significant amount of time looking for information and often fail to leverage the information they have. In response, many organizations have deployed some form of enterprise search to improve the "findability" of information. Debates persist as to whether thesauri and manual indexing or automated machine learning techniques should be used to enhance discovery of information. In addition, the extent to which a knowledge organization system (KOS) enhances discoveries or indeed blinds us to new ones remains a moot point. The oil and gas industry was used as a case study using a representative organization. Drawing on prior research, a theoretical model is presented which aims to overcome the shortcomings of each approach. This synergistic model could help to re-conceptualize the "manual" versus "automatic" debate in many enterprises, accommodating a broader range of information needs. This may enable enterprises to develop more effective information and knowledge management strategies and ease the tension between what are often perceived as mutually exclusive competing approaches. Certain aspects of the theoretical model may be transferable to other industries, which is an area for further research. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Knowledge Organization is the property of IMR Press 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.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=111161605 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.5771/0943-7444-2015-6-428 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 428 Subjects: – SubjectFull: Computers Type: general – SubjectFull: Computerized typesetting Type: general – SubjectFull: Knowledge management Type: general – SubjectFull: Computer science Type: general – SubjectFull: Information storage & retrieval systems in the petroleum industry Type: general Titles: – TitleFull: The Best of Both Worlds: Highlighting the Synergies of Combining Manual and Automatic Knowledge Organization Methods to Improve Information Search and Discovery. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cleverley, Paul H. – PersonEntity: Name: NameFull: Burnett, Simon IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: 2015 Type: published Y: 2015 Identifiers: – Type: issn-print Value: 09437444 Numbering: – Type: volume Value: 42 – Type: issue Value: 6 Titles: – TitleFull: Knowledge Organization Type: main |
| ResultId | 1 |
