LEADER 04129nam 2200841 450 001 9910460186703321 005 20210429194131.0 010 $a3-11-036381-X 010 $a3-11-039317-4 024 7 $a10.1515/9783110363814 035 $a(CKB)3710000000359857 035 $a(EBL)1897882 035 $a(SSID)ssj0001457406 035 $a(PQKBManifestationID)11822858 035 $a(PQKBTitleCode)TC0001457406 035 $a(PQKBWorkID)11441467 035 $a(PQKB)10045665 035 $a(MiAaPQ)EBC1897882 035 $a(DE-B1597)426889 035 $a(OCoLC)1013948543 035 $a(OCoLC)1037981870 035 $a(OCoLC)1042024853 035 $a(OCoLC)1046610358 035 $a(OCoLC)1047001902 035 $a(OCoLC)1049145067 035 $a(OCoLC)1054880222 035 $a(OCoLC)904454427 035 $a(DE-B1597)9783110363814 035 $a(PPN)204465818 035 $a(Au-PeEL)EBL1897882 035 $a(CaPaEBR)ebr11049312 035 $a(CaONFJC)MIL808017 035 $a(OCoLC)907650339 035 $a(EXLCZ)993710000000359857 100 $a20140929h20152015 uy| 0 101 0 $aeng 135 $aur|nu---|u||u 181 $ctxt 182 $cc 183 $acr 200 10$aCluster analysis for corpus linguistics /$fby Hermann Moisl 210 1$aBerlin ;$aBoston :$cDe Gruyter,$d[2015] 210 4$dİ2015 215 $a1 online resource (398 p.) 225 1 $aQuantitative linguistics ;$v66 300 $aDescription based upon print version of record. 311 $a3-11-036382-8 311 $a3-11-035025-4 320 $aIncludes bibliographical references (pages 311-358) and index. 327 $tFront matter --$tPreface --$tContents --$tList of figures --$t1. Introduction --$t2. Motivation --$t3. Data --$t4. Cluster --$t5. Hypothesis generation --$t6. Literature Review --$t7. Conclusion --$t8. Appendix --$tReferences --$tSubject index 330 $aThe standard scientific methodology in linguistics is empirical testing of falsifiable hypotheses. As such the process of hypothesis generation is central, and involves formulation of a research question about a domain of interest and statement of a hypothesis relative to it. In corpus linguistics the domain is text, and generation involves abstraction of data from text, data analysis, and formulation of a hypothesis based on inference from the results. Traditionally this process has been paper-based, but the advent of electronic text has increasingly rendered it obsolete both because the size of digital corpora is now at or beyond the limit of what can efficiently be used in the traditional way, and because the complexity of data abstracted from them can be impenetrable to understanding. Linguists are increasingly turning to mathematical and statistical computational methods for help, and cluster analysis is such a method. It is used across the sciences for hypothesis generation by identification of structure in data which are too large or complex, or both, to be interpretable by direct inspection. This book aims to show how cluster analysis can be used for hypothesis generation in corpus linguistics, thereby contributing to a quantitative empirical methodology for the discipline. 410 0$aQuantitative linguistics ;$v66. 606 $aCorpora (Linguistics)$xData processing 606 $aCluster analysis$xData processing 606 $aNatural language processing (Computer science) 606 $aQuantitative linguistics 606 $aComputational linguistics 608 $aElectronic books. 615 0$aCorpora (Linguistics)$xData processing. 615 0$aCluster analysis$xData processing. 615 0$aNatural language processing (Computer science) 615 0$aQuantitative linguistics. 615 0$aComputational linguistics. 676 $a410.1/880151953 686 $aES 900$2rvk 700 $aMoisl$b Hermann$f1949-$0777388 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460186703321 996 $aCluster analysis for corpus linguistics$92461113 997 $aUNINA