Blending Machine Learning and Interaction Design in Audio Explorer.
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| Title: | Blending Machine Learning and Interaction Design in Audio Explorer. |
|---|---|
| Authors: | Scruggs, Colin1 (AUTHOR), Henkel, Cameron2 (AUTHOR), Stolper, Charles3 (AUTHOR), Cook, Kris4 (AUTHOR), Crouser, R. Jordan5 (AUTHOR) |
| Source: | IEEE Computer Graphics & Applications. Mar/Apr2021, Vol. 41 Issue 2, p89-95. 7p. |
| Subjects: | Microsoft Internet explorer (Computer software), Machine learning, Data visualization, Explorers, Task analysis |
| Abstract: | The results of machine learning models can often be difficult to interpret, especially for domain experts. Audio Explorer, the winning entry of the 2018 VAST Challenge, is an interactive data exploration tool that effectively communicates machine learning results using coordinated geospatial, temporal, and auditory visualizations to promote information discovery. [ABSTRACT FROM AUTHOR] |
| Copyright of IEEE Computer Graphics & Applications is the property of IEEE 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 | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 149417822 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Blending Machine Learning and Interaction Design in Audio Explorer. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Scruggs%2C+Colin%22">Scruggs, Colin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Henkel%2C+Cameron%22">Henkel, Cameron</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Stolper%2C+Charles%22">Stolper, Charles</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cook%2C+Kris%22">Cook, Kris</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Crouser%2C+R%2E+Jordan%22">Crouser, R. Jordan</searchLink><relatesTo>5</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Computer+Graphics+%26+Applications%22">IEEE Computer Graphics & Applications</searchLink>. Mar/Apr2021, Vol. 41 Issue 2, p89-95. 7p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Microsoft+Internet+explorer+%28Computer+software%29%22">Microsoft Internet explorer (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Data+visualization%22">Data visualization</searchLink><br /><searchLink fieldCode="DE" term="%22Explorers%22">Explorers</searchLink><br /><searchLink fieldCode="DE" term="%22Task+analysis%22">Task analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The results of machine learning models can often be difficult to interpret, especially for domain experts. Audio Explorer, the winning entry of the 2018 VAST Challenge, is an interactive data exploration tool that effectively communicates machine learning results using coordinated geospatial, temporal, and auditory visualizations to promote information discovery. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Computer Graphics & Applications is the property of IEEE 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=149417822 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/MCG.2019.2950185 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 7 StartPage: 89 Subjects: – SubjectFull: Microsoft Internet explorer (Computer software) Type: general – SubjectFull: Machine learning Type: general – SubjectFull: Data visualization Type: general – SubjectFull: Explorers Type: general – SubjectFull: Task analysis Type: general Titles: – TitleFull: Blending Machine Learning and Interaction Design in Audio Explorer. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Scruggs, Colin – PersonEntity: Name: NameFull: Henkel, Cameron – PersonEntity: Name: NameFull: Stolper, Charles – PersonEntity: Name: NameFull: Cook, Kris – PersonEntity: Name: NameFull: Crouser, R. Jordan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar/Apr2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 02721716 Numbering: – Type: volume Value: 41 – Type: issue Value: 2 Titles: – TitleFull: IEEE Computer Graphics & Applications Type: main |
| ResultId | 1 |
