LEADER 03854nam 2200625 450 001 9910788824603321 005 20230807210923.0 010 $a3-11-039477-4 010 $a3-11-036287-2 024 7 $a10.1515/9783110362879 035 $a(CKB)3360000000515260 035 $a(EBL)1867281 035 $a(SSID)ssj0001457615 035 $a(PQKBManifestationID)11782711 035 $a(PQKBTitleCode)TC0001457615 035 $a(PQKBWorkID)11441235 035 $a(PQKB)10408199 035 $a(MiAaPQ)EBC1867281 035 $a(DE-B1597)426729 035 $a(OCoLC)908670253 035 $a(DE-B1597)9783110362879 035 $a(Au-PeEL)EBL1867281 035 $a(CaPaEBR)ebr11049686 035 $a(CaONFJC)MIL808133 035 $a(EXLCZ)993360000000515260 100 $a20150324h20152015 uy| 0 101 0 $aeng 135 $aur||#|||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aSequences in language and text /$fedited by George K. Mikros, Ja?n Macutek 210 1$aBerlin ;$aBoston :$cDe Gruyter Mouton,$d[2015] 210 4$dİ2015 215 $a1 online resource (268 p.) 225 1 $aQuantitative linguistics ;$vQl69 300 $aDescription based upon print version of record. 311 $a3-11-036273-2 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tForeword --$tContents --$tIntroduction --$tLinguistic Analysis Based on Fuzzy Similarity Models --$tTextual navigation and autocorrelation --$tMenzerath-Altmann law versus random model --$tText length and the lambda frequency structure of a text --$tLinguistic Motifs --$tLinguistic Modelling of Sequential Phenomena --$tMenzerath-Altmann Law for Word Length Motifs --$tIs the Distribution of L-Motifs Inherited from the Word Length Distribution? --$tSequential Structures in ?Dalimil?s Chronicle? --$tComparative Evaluation of String Similarity Measures for Automatic Language Classification --$tPredicting Sales Trends --$tWhere Alice Meets Little Prince --$tA Probabilistic Model for the Arc Length in Quantitative Linguistics --$tSubject Index --$tAuthors Index --$tAuthors? addresses 330 $aThe edited volume Sequences in Language and Text is the first collection of original research in the area of the quantitative analysis of sequentially organized linguistic data. Linguistic sequences are extremely useful textual structures in almost all areas of Language Technology. Character and word n-grams are by far the most successful features in text classification tasks such as authorship identification, text categorization, genre classification, sentiment analysis etc. Furthermore character linguistic sequences are the basis for linguistic modeling and subsequent applications such as speech recognition, language identification etc. In addition to the above language technology oriented research, the present volume aims to give insight to the theoretical value of linguistic sequences. Sequences in texts can be produced by a number of different factors, either external to the linguistic system or by its own grammatical structure. This volume hosts contributions which will analyze linguistic sequences using quantitative methods under the synergetic theoretical framework that can explain their role in the linguistic system. 410 0$aQuantitative linguistics ;$vQl69. 606 $aComputational linguistics$xResearch 610 $aQuantitative Linguistics, Sequence Analysis, Mathematical Linguistics. 615 0$aComputational linguistics$xResearch. 676 $a006.3/5 702 $aMikros$b George K.$f1969- 702 $aMac?utek$b Ja?n 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910788824603321 996 $aSequences in language and text$93764902 997 $aUNINA