Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis

Funding institutions often solicit text-based research proposals to evaluate potential recipients. Leveraging the information contained in these documents could help institutions understand the supply of research within their domain. In this work, an end-to-end methodology for semi-supervised docume...

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Vydáno v:	Scientometrics Ročník 128; číslo 5; s. 3197 - 3224
Hlavní autoři:	Knisely, Benjamin M., Pavliscsak, Holly H.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.05.2023 Springer Nature B.V
Témata:	Algorithms Annotations Army Averages Bidirectionality Classification Clustering Coherence Comparative analysis Computer Science Distinctiveness Documents Embedding Extraction Funding Information Storage and Retrieval Innovations Institutions Library Science Machine learning Medical technology Medicine Methodology Military technology Natural language processing Proposals Ratings Ratings & rankings Research facilities Research methodology Research proposals Subject specialists Technological change Telecommunications Telemedicine Trends Text mining Cluster validation Document clustering Research portfolio Machine learning
ISSN:	0138-9130, 1588-2861
On-line přístup:	Získat plný text
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