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010   $a1-119-28210-1
035   $a(CKB)4330000000009928
035   $a(DLC)  2017010584
035   $a(Au-PeEL)EBL4860512
035   $a(CaPaEBR)ebr11385346
035   $a(CaONFJC)MIL1011172
035   $a(PPN)236707949
035   $a(MiAaPQ)EBC4860512
035   $a(OCoLC)974796237
035   $a(EXLCZ)994330000000009928
100   $a20170606h20172017  uy             0
101 0 $aeng
135   $aurcnu||||||||
181   $2rdacontent
182   $2rdamedia
183   $2rdacarrier
200 10$aText mining in practice with R /$fTed Kwartler
210  1$aChichester, England :$cWiley,$d2017.
210  4$dİ2017
215   $a1 online resource (309 pages) $cillustrations
225 1 $aTHEi Wiley ebooks
300   $aIncludes index.
311   $a1-119-28201-2 
327   $aWhat is text mining? -- Basics of text mining -- Common text mining visualizations -- Sentiment scoring -- Hidden structures : clustering, string distance, text vectors & topic modeling -- Document classification : finding clickbait from headlines -- Predictive modeling : using text for classifying & predicting outcomes -- The OpenNLP Project -- Text sources.
410  0$aTHEi Wiley ebooks.
606   $aR (Computer program language)
606   $aData mining
606   $aText processing (Computer science)
615  0$aR (Computer program language).
615  0$aData mining.
615  0$aText processing (Computer science)
676   $a006.3/12
700   $aKwartler$b Ted$f1978-$01676161
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910812215203321
996   $aText mining in practice with R$94042181
997   $aUNINA