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Visit USCOMachine Learning (ML) for Tracking the Geo-Temporality of a Trend: Documenting the Frequency of the Baseball-Trucker Hat on Social Media and the Runway
Text Registration
Copyright Title
Machine Learning (ML) for Tracking the Geo-Temporality of a Trend: Documenting the Frequency of the Baseball-Trucker Hat on Social Media and the Runway
Status
Published
on 21 Jun 2019
Year of Creation
2019
Copyright Claimant
Rachel Rose Getman
Registration Number
TX0008763333
on 21 Jun 2019Copyright Summary
The U.S. Copyright record (Registration Number: TX0008763333) dated 21 Jun 2019, pertains to an electronic file (eService) titled "Machine Learning (ML) for Tracking the Geo-Temporality of a Trend: Documenting the Frequency of the Baseball-Trucker Hat on Social Media and the Runway" created in 2019. The copyright holder is Rachel Rose Getman, known for their creative contributions in text registration. For any inquiries concerning this copyrighted material, kindly reach out to Rachel Rose Getman.
Application Details
Registration Number
TX0008763333
Registration Date
6/21/2019
Year of Creation
2019
Agency Marc Code
DLC-CO
Record Status
New
Physical Description
Electronic file (eService)
First Publication Nation
United States
Notes
Rights Note: Mark Dill, ProQuest-CSA, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com
Statements
Application Title Statement: Machine Learning (ML) for Tracking the Geo-Temporality of a Trend: Documenting the Frequency of the Baseball-Trucker Hat on Social Media and the Runway
Author Statement: Rachel Rose Getman Citizenship: not known Authorship: text
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