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  4. An organizational approach for discipline prediction in research projects

An organizational approach for discipline prediction in research projects

Author(s)
Keywords

research information ...

research projects

research classificati...

metadata quality

discipline prediction...

ECOOM

Issue Date
May 31, 2023
Publisher
euroCRIS
Type
Presentation
Abstract
The prediction of research disciplines has gained increasing attention in recent years due to its potential implementations in a variety of fields, such as academic advising, career counseling, and academic research funding allocation. Research information systems storing projects (meta) data play a crucial role in managing and evaluating research (meta)data across different disciplines and fields of study. In this context, research projects are manually assigned one or more research disciplines to facilitate this process. This is usually done by research administrators due to the limited time the principal researchers themselves might have. In addition to being rather subjective and time-consuming, this can lead to inconsistencies in discipline assignments and hence impact the quality of data used for monitoring and reporting.
Description
22 slides.-- Presentation delivered by Hoang-Son Pham within the "National session (II)".-- Includes extended abstract submitted to the event
URI
https://dspacecris.eurocris.org/handle/11366/2456
File(s)
Thumbnail Image
Name

MM2023Brussels_proposal_Resproj_discipline_prediction_ECOOM_UHasselt.pdf

Description
Extended abstract
Size

87.31 KB

Format

Adobe PDF

Checksum (MD5)

53c441b7cab3b415612932d3ac4e4036

Thumbnail Image
Name

euroCRIS_MM2023Brussels_slides_project-discipline-prediction_UHasselt_20230531.pdf

Description
PDF presentation
Size

283.13 KB

Format

Adobe PDF

Checksum (MD5)

2989e899a8906e9776c8577ab00756bc

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