LEADER 01822cam0-2200517---450 001 990004201650403321 005 20210519134018.0 035 $a000420165 100 $a19990604d1925----km-y0itay50------ba 101 0 $ager 102 $aDE 105 $aaf y 001yy 200 1 $aAltfranzösisches Wörterbuch$fTobler-Lommatzsch$gAdolf Toblers nachgelassene Materialen bearbeitet und mit Unterstützung der Preussische Akademie der Wissenschaften herausgegeben von Erhard Lommatzsch 210 $aBerlin$cVeidmamsche Buchlandung$aWiesbaden$cSteiner$d1925- 215 $av.$d29 cm 610 0 $aLingua francese antica$aDizionari 676 $a447.0103 700 1$aTobler,$bAdolf$f<1835-1910>$0164896 701 1$aLommatzsch,$bErhard$0164897 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004201650403321 952 $a447.0103 TOB 1(1)$fFLFBC 952 $a447.0103 TOB 1(2)$fFLFBC 952 $a447.0103 TOB 1(3)$fFLFBC 952 $a447.0103 TOB 1(4)$fFLFBC 952 $a447.0103 TOB 1(5)$fFLFBC 952 $a447.0103 TOB 1(6)$fFLFBC 952 $a447.0103 TOB 1(7)$fFLFBC 952 $a447.0103 TOB 1(8)$fFLFBC 952 $a447.0103 TOB 1(9)$fFLFBC 952 $a447.0103 TOB 1(10)$fFLFBC 952 $a447.0103 TOB 1(11)$fFLFBC 952 $a447.0103 TOB 1(1 BIS)$fFLFBC 952 $a447.0103 TOB 1(2 BIS)$fFLFBC 952 $a447.0103 TOB 1(3 BIS)$fFLFBC 952 $a447.0103 TOB 1(4 BIS)$fFLFBC 952 $a447.0103 TOB 1(5 BIS)$fFLFBC 952 $a447.0103 TOB 1(6 BIS)$fFLFBC 952 $a447.0103 TOB 1(7 BIS)$fFLFBC 952 $a447.0103 TOB 1(8 BIS)$fFLFBC 952 $a447.0103 TOB 1(9 BIS)$fFLFBC 952 $a447.0103 TOB 1(10 BIS)$fFLFBC 959 $aFLFBC 996 $aAltfranzösisches Wörterbuch$9483591 997 $aUNINA LEADER 01195nam 2200349 n 450 001 996387798703316 005 20221108031304.0 035 $a(CKB)1000000000628432 035 $a(EEBO)2240902285 035 $a(UnM)99861156 035 $a(EXLCZ)991000000000628432 100 $a19920306d1656 uy | 101 0 $alat 135 $aurbn||||a|bb| 200 10$aAdenographia: sive, glandularum totius corporis descriptio$b[electronic resource] /$fAuthore Thoma? 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[1656] 215 $a[18], 287, [1] p., plates $cill 300 $aWith an errata leaf, sometimes bound at end. 300 $aAnnotation on Thomason copy: "nou: 3". 300 $aReproduction of the original in the British Library. 330 $aeebo-0018 606 $aMedicine$vEarly works to 1800 615 0$aMedicine 700 $aWharton$b Thomas$f1614-1673.$01009472 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bWaOLN 906 $aBOOK 912 $a996387798703316 996 $aAdenographia: sive, glandularum totius corporis descriptio$92422329 997 $aUNISA LEADER 00800nam0-22002771i-450 001 990002742860403321 005 20230710110419.0 035 $a000274286 035 $aFED01000274286 035 $a(Aleph)000274286FED01 100 $a20000920d1962----km-y0itay50------ba 101 0 $aita 102 $aIT 200 1 $aComputisteria.$fdi Ugo Monetti. 205 $a18 ed. aggiornata con le più recenti disposizioni 210 $aRoma$cDella Rivista Italiana Ragioneria$d1962 215 $a323 p.$d17 cm 225 1 $aNuovissimo compendio di computisteria e ragioneria 700 1$aMonetti,$bUgo$0370449 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002742860403321 952 $aC2-P43-42-RA$bs.i.$fECA 959 $aECA 996 $aComputisteria$9425676 997 $aUNINA LEADER 03644nam 22005295 450 001 9910299459603321 005 20200705065051.0 010 $a3-319-73531-4 024 7 $a10.1007/978-3-319-73531-3 035 $a(CKB)4100000002892262 035 $a(DE-He213)978-3-319-73531-3 035 $a(MiAaPQ)EBC6314099 035 $a(MiAaPQ)EBC5589130 035 $a(Au-PeEL)EBL5589130 035 $a(OCoLC)1029870455 035 $a(PPN)225553392 035 $a(EXLCZ)994100000002892262 100 $a20180319d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning for Text /$fby Charu C. Aggarwal 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XXIII, 493 p. 80 illus., 4 illus. in color.) 311 $a3-319-73530-6 327 $a1 An Introduction to Text Analytics -- 2 Text Preparation and Similarity Computation -- 3 Matrix Factorization and Topic Modeling -- 4 Text Clustering -- 5 Text Classification: Basic Models -- 6 Linear Models for Classification and Regression -- 7 Classifier Performance and Evaluation -- 8 Joint Text Mining with Heterogeneous Data -- 9 Information Retrieval and Search Engines -- 10 Text Sequence Modeling and Deep Learning -- 11 Text Summarization -- 12 Information Extraction -- 13 Opinion Mining and Sentiment Analysis -- 14 Text Segmentation and Event Detection. 330 $aText analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorithms: Chapters 1 through 8 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This book covers text analytics and machine learning topics from the simple to the advanced. Since the coverage is extensive, multiple courses can be offered from the same book, depending on course level. 606 $aData mining 606 $aArtificial intelligence 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aData mining. 615 0$aArtificial intelligence. 615 14$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 676 $a006.31 700 $aAggarwal$b Charu C$4aut$4http://id.loc.gov/vocabulary/relators/aut$0518673 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299459603321 996 $aMachine Learning for Text$92175811 997 $aUNINA