Academic Journal
Visualising hierarchical associations.
| Τίτλος: | Visualising hierarchical associations. |
|---|---|
| Συγγραφείς: | Ceglar, Aaron, Roddick, John, Calder, Paul, Rainsford, Chris |
| Πηγή: | Knowledge & Information Systems; Sep2005, Vol. 8 Issue 3, p257-275, 19p, 18 Diagrams |
| Θεματικοί όροι: | Visualization, Abstract thought, Data mining, Database searching, Algorithms |
| Περίληψη: | Recent association-mining research has led to the development of techniques that allow the accommodation of concept hierarchies within the mining process. This extension results in the discovery of rules which associate not only groups of items but which are also influenced by the hierarchies within which an item may reside. Given this, there then arises a need for techniques whereby such hierarchical associations can be presented to the user. Current association rule visualisation techniques are limited, as they do not effectively incorporate or enable the visualisation of hierarchical semantics. This paper presents a review of current hierarchical and association visualisation techniques and introduces a novel technique for visualising hierarchical association rules. [ABSTRACT FROM AUTHOR] |
| Copyright of Knowledge & Information Systems is the property of Springer Nature 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.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://dx.doi.org/doi:10.1007/s10115-003-0139-0 Name: EDS - Springer Nature Journals (s7799221) Category: fullText Text: View record at Springer |
|---|---|
| Header | DbId: edb DbLabel: Complementary Index An: 18070558 RelevancyScore: 832 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 832.352294921875 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Visualising hierarchical associations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ceglar%2C+Aaron%22">Ceglar, Aaron</searchLink><br /><searchLink fieldCode="AR" term="%22Roddick%2C+John%22">Roddick, John</searchLink><br /><searchLink fieldCode="AR" term="%22Calder%2C+Paul%22">Calder, Paul</searchLink><br /><searchLink fieldCode="AR" term="%22Rainsford%2C+Chris%22">Rainsford, Chris</searchLink> – Name: TitleSource Label: Source Group: Src Data: Knowledge & Information Systems; Sep2005, Vol. 8 Issue 3, p257-275, 19p, 18 Diagrams – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Visualization%22">Visualization</searchLink><br /><searchLink fieldCode="DE" term="%22Abstract+thought%22">Abstract thought</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink><br /><searchLink fieldCode="DE" term="%22Database+searching%22">Database searching</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Recent association-mining research has led to the development of techniques that allow the accommodation of concept hierarchies within the mining process. This extension results in the discovery of rules which associate not only groups of items but which are also influenced by the hierarchies within which an item may reside. Given this, there then arises a need for techniques whereby such hierarchical associations can be presented to the user. Current association rule visualisation techniques are limited, as they do not effectively incorporate or enable the visualisation of hierarchical semantics. This paper presents a review of current hierarchical and association visualisation techniques and introduces a novel technique for visualising hierarchical association rules. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Knowledge & Information Systems is the property of Springer Nature 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=edb&AN=18070558 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10115-003-0139-0 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 257 Subjects: – SubjectFull: Visualization Type: general – SubjectFull: Abstract thought Type: general – SubjectFull: Data mining Type: general – SubjectFull: Database searching Type: general – SubjectFull: Algorithms Type: general Titles: – TitleFull: Visualising hierarchical associations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ceglar, Aaron – PersonEntity: Name: NameFull: Roddick, John – PersonEntity: Name: NameFull: Calder, Paul – PersonEntity: Name: NameFull: Rainsford, Chris IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2005 Type: published Y: 2005 Identifiers: – Type: issn-print Value: 02191377 Numbering: – Type: volume Value: 8 – Type: issue Value: 3 Titles: – TitleFull: Knowledge & Information Systems Type: main |
| ResultId | 1 |