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https://ruomo.lib.uom.gr/handle/7000/1154| Title: | Document clustering via multiple correspondence, term and metadata analysis in R |
| Authors: | Koutsoupias, Nikos Mikelis, Kyriakos |
| Type: | Other |
| Subjects: | FRASCATI::Natural sciences::Computer and information sciences |
| Keywords: | document clustering hierarchical clustering multiple correspondence analysis document metadata text mining |
| Issue Date: | 2019 |
| Source: | 2019 IFCS CONFERENCE |
| Volume: | 16th Conference of the International Federation of Classification Societies |
| Abstract: | We introduce the combined use of multiple correspondence analysis, metadata and term frequencies for clustering articles of a scientific journal. A period of five years (2010-2014) is covered, with approximately 125 articles. Through specific R packages for multidimensional data analysis and text mining, the approach links quantitative analysis of discourse to clustering documents considering both metadata and frequent terms. |
| URI: | https://www.researchgate.net/publication/335665535_Document_Clustering_via_Multiple_Correspondence_Term_and_Metadata_Analysis_in_R https://ruomo.lib.uom.gr/handle/7000/1154 |
| Other Identifiers: | 10.13140/RG.2.2.22716.59527 |
| Appears in Collections: | Department of International and European Studies |
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