Please use this identifier to cite or link to this item:
http://hdl.handle.net/11366/2456
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Pham, Hoang-Son | en_US |
dc.contributor.author | Eldin, Amr Ali | en_US |
dc.contributor.author | Poelmans, Hanne | en_US |
dc.date.accessioned | 2023-06-04T18:48:10Z | - |
dc.date.available | 2023-06-04T18:48:10Z | - |
dc.date.issued | 2023-05-31 | - |
dc.identifier.uri | http://hdl.handle.net/11366/2456 | - |
dc.description | 22 slides.-- Presentation delivered by Hoang-Son Pham within the "National session (II)".-- Includes extended abstract submitted to the event | en_US |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | euroCRIS | en_US |
dc.subject | research information management | en_US |
dc.subject | research projects | en_US |
dc.subject | research classifications | en_US |
dc.subject | metadata quality | en_US |
dc.subject | discipline prediction | en_US |
dc.subject | ECOOM | en_US |
dc.title | An organizational approach for discipline prediction in research projects | en_US |
dc.type | Presentation | en_US |
dc.relation.conference | Membership Meeting 2023 – Spring (Brussels) | en_US |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
item.openairetype | Presentation | - |
item.fulltext | With Fulltext | - |
item.languageiso639-1 | en | - |
Appears in Collections: | Conference |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
euroCRIS_MM2023Brussels_slides_project-discipline-prediction_UHasselt_20230531.pdf | PDF presentation | 283.12 kB | Adobe PDF | View/Open |
MM2023Brussels_proposal_Resproj_discipline_prediction_ECOOM_UHasselt.pdf | Extended abstract | 87.31 kB | Adobe PDF | View/Open |
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