LEADER 06084nam 22008055 450 001 996465985103316 005 20200702140125.0 010 $a3-642-35828-4 024 7 $a10.1007/978-3-642-35828-9 035 $a(CKB)3400000000102962 035 $a(SSID)ssj0000855337 035 $a(PQKBManifestationID)11488154 035 $a(PQKBTitleCode)TC0000855337 035 $a(PQKBWorkID)10912549 035 $a(PQKB)10145606 035 $a(DE-He213)978-3-642-35828-9 035 $a(MiAaPQ)EBC3068802 035 $a(PPN)168329387 035 $a(EXLCZ)993400000000102962 100 $a20130107d2013 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aEvaluation of Natural Language and Speech Tool for Italian$b[electronic resource] $eInternational Workshop, EVALITA 2011, Rome, January 24-25, 2012, Revised Selected Papers /$fedited by Bernardo Magnini, Francesco Cutugno, Mauro Falcone, Emanuele Pianta 205 $a1st ed. 2013. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013. 215 $a1 online resource (XIV, 339 p. 38 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v7689 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-35827-6 320 $aIncludes bibliographical references and index. 327 $aThe EVALITA Dependency Parsing Task: From 2007 to 2011 -- Use of Semantic Information in a Syntactic Dependency Parser -- Parsit at Evalita 2011 Dependency Parsing Task -- An Ensemble Model for the EVALITA 2011 Dependency Parsing Task -- Tuning DeSR for Dependency Parsing of Italian -- Domain Adaptation for Dependency Parsing at Evalita 2011 -- Experiments in Newswire-to-Law Adaptation of Graph-Based Dependency Parsers -- Domain Adaptation by Active Learning -- Named Entity Recognition on Transcribed Broadcast News at EVALITA 2011 -- A Simple Yet Effective Approach for Named Entity Recognition from Transcribed Broadcast News -- The Tanl Tagger for Named Entity Recognition on Transcribed Broadcast News at Evalita 2011 -- The News People Search Task at EVALITA 2011: Evaluating Cross-Document Coreference Resolution of Named Person Entities in Italian News -- Exploiting Background Knowledge for Clustering Person Names -- Description and Results of the SuperSense Tagging Task -- Super-Sense Tagging Using Support Vector Machines and Distributional Features -- Generative and Discriminative Learning in Semantic Role Labeling for Italian -- Structured Kernel-Based Learning for the Frame Labeling over Italian Texts -- The Lemmatisation Task at the EVALITA 2011 Evaluation Campaign -- The Vocapia Research ASR Systems for Evalita 2011 -- The SPPAS Participation to the Forced-Alignment Task -- SAD-Based Italian Forced Alignment Strategies. 330 $aEVALITA (http://www.evalita.it/) is the reference evaluation campaign of both Natural Language Processing and Speech Technologies for the Italian language. The objective of the shared tasks proposed at EVALITA is to promote the development of language technologies for Italian, providing a common framework where different systems and approaches can be evaluated and compared in a consistent manner. This volume collects the final and extended contributions presented at EVALITA 2011, the third edition of the evaluation campaign. The 36 revised full papers were carefully reviewed and selected from a total of 87 submissions. The papers are organized in topical sections roughly corresponding to evaluation tasks: parsing - dependency parsing track, parsing - constituency parsing track, domain adaptation for dependency parsing, named entity recognition on transcribed broadcast news, cross-document coreference resolution of named person entities, anaphora resolution, supersense tagging, frame labeling over italian texts, lemmatisation, automatic speech recognition - large vocabulary transcription, forced alignment on spontaneous speech. 410 0$aLecture Notes in Artificial Intelligence ;$v7689 606 $aArtificial intelligence 606 $aNatural language processing (Computer science) 606 $aRomance languages 606 $aDatabase management 606 $aPattern recognition 606 $aInformation storage and retrieval 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aRomance Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/N36000 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 615 0$aArtificial intelligence. 615 0$aNatural language processing (Computer science). 615 0$aRomance languages. 615 0$aDatabase management. 615 0$aPattern recognition. 615 0$aInformation storage and retrieval. 615 14$aArtificial Intelligence. 615 24$aNatural Language Processing (NLP). 615 24$aRomance Languages. 615 24$aDatabase Management. 615 24$aPattern Recognition. 615 24$aInformation Storage and Retrieval. 676 $a006.3/5 702 $aMagnini$b Bernardo$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aCutugno$b Francesco$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFalcone$b Mauro$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPianta$b Emanuele$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aEVALITA 2011 906 $aBOOK 912 $a996465985103316 996 $aEvaluation of Natural Language and Speech Tool for Italian$92830914 997 $aUNISA LEADER 03381nam 2200769 450 001 996212659803316 005 20230120124050.0 010 $a1-282-81959-3 010 $a9786612819599 010 $a1-897425-46-5 035 $a(CKB)2550000000010267 035 $a(EBL)624082 035 $a(OCoLC)646836784 035 $a(SSID)ssj0000415727 035 $a(PQKBManifestationID)11311555 035 $a(PQKBTitleCode)TC0000415727 035 $a(PQKBWorkID)10411188 035 $a(PQKB)10018918 035 $a(CaPaEBR)432544 035 $a(CaBNvSL)slc00223185 035 $a(Au-PeEL)EBL4837940 035 $a(CaPaEBR)ebr11372205 035 $a(OCoLC)983738703 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/44825 035 $a(VaAlCD)20.500.12592/gfv8f9 035 $a(MiAaPQ)EBC4837940 035 $a(EXLCZ)992550000000010267 100 $a20170425h20092009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 12$aA designer's log $ecase studies in instructional design /$fby Michael Power 210 $cAthabasca University Press$d2009 210 1$aEdmonton, Alberta :$cAU Press,$d2009. 210 4$dİ2009 215 $a1 online resource (267 pages) $cillustrations 225 1 $aIssues in Distance Education 300 $aTranslation of: Le conseiller pe?dagogique re?flexif. 311 $a1-897425-61-9 320 $aIncludes bibliographical references and index. 327 $aCover; Front Matter; Contents; Foreword; Preface; Introduction; The Case Studies; Case Study 1: Walking the Walk; Case Study 2: Beating the Clock; Case Study 3: Experiencing a Eureka! Moment; Case Study 4: Getting Off to a Good Start; Case Study 5: Getting from A to B; Case Study 6: I Did It My Way; Case Study 7: Let's Shake to That!; Case Study 8: Managing Volume; Case Study 9: I and Thou; Case Study 10: Integrating Technology; Synthesis and Final Prototype; Conclusion; Epilogue; Bibliography; Appendix A; Appendix B 330 $aBooks and articles on instructional design in online learning abound but rarely do we get such a comprehensive picture of what instructional designers do, how they do it, and the problems they solve as their university changes. Power documents the emergence of an adapted instructional design model for transforming courses from single-mode to dual-mode instruction, making this designer's log a unique contribution to the fi eld of online learning. 606 $aUniversities and colleges$xCurricula$xPlanning 606 $aInstructional systems$xDesign 606 $aCurriculum planning 606 $aUniversities and colleges$xCurricula$xPlanning$vCase studies 606 $aDistance education 610 $aeducation 610 $ainstructional design 610 $aonline learning 610 $adistance learning 615 0$aUniversities and colleges$xCurricula$xPlanning. 615 0$aInstructional systems$xDesign. 615 0$aCurriculum planning. 615 0$aUniversities and colleges$xCurricula$xPlanning 615 0$aDistance education. 676 $a378.1/99 700 $aPower$b Michael$0155423 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996212659803316 996 $aA designer's log$92104473 997 $aUNISA