Textual Data Science with R:
Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by app...
Saved in:
| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Boca Raton
CRC Press, Taylor & Francis Group
2021
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| Series: | Chapman & Hall/CRC Computer Science & Data Analysis Series
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| Subjects: | |
| Summary: | Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential |
| Physical Description: | xvii, 194 Seiten Illustrationen, Diagramme |
| ISBN: | 9781032093659 9781138626911 |
Staff View
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| institution | BVB |
| isbn | 9781032093659 9781138626911 |
| language | English |
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| physical | xvii, 194 Seiten Illustrationen, Diagramme |
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| spelling | Bécue-Bertaut, Mónica Verfasser (DE-588)1238916554 aut Textual Data Science with R Mónica Bécue-Bertaut Boca Raton CRC Press, Taylor & Francis Group 2021 xvii, 194 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC Computer Science & Data Analysis Series Textual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential Text Mining (DE-588)4728093-1 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Text Mining (DE-588)4728093-1 s R Programm (DE-588)4705956-4 s DE-604 |
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| title | Textual Data Science with R |
| title_auth | Textual Data Science with R |
| title_exact_search | Textual Data Science with R |
| title_exact_search_txtP | Textual Data Science with R |
| title_full | Textual Data Science with R Mónica Bécue-Bertaut |
| title_fullStr | Textual Data Science with R Mónica Bécue-Bertaut |
| title_full_unstemmed | Textual Data Science with R Mónica Bécue-Bertaut |
| title_short | Textual Data Science with R |
| title_sort | textual data science with r |
| topic | Text Mining (DE-588)4728093-1 gnd R Programm (DE-588)4705956-4 gnd |
| topic_facet | Text Mining R Programm |
| work_keys_str_mv | AT becuebertautmonica textualdatasciencewithr |