LEADER 02459nam 2200409 450 001 9910480790003321 005 20210901203039.0 010 $a1-5275-1951-1 035 $a(CKB)4100000007121609 035 $a(MiAaPQ)EBC5568613 035 $a(Au-PeEL)EBL5568613 035 $a(OCoLC)1061125736 035 $a(EXLCZ)994100000007121609 100 $a20181123d2018 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 04$aThe explicit and the implicit in language and speech /$fedited by Liudmila Liashchova 210 1$aNewcastle upon Tyne, England :$cCambridge Scholars Publishing,$d2018. 215 $a1 online resource (327 pages) 311 $a1-5275-1638-5 327 $aIntro -- Contents -- Preface and Acknowledgements -- Introduction -- Part I -- Chapter One -- Chapter Two -- Chapter Three -- Chapter Four -- Chapter Five -- Chapter Six -- Part II -- Chapter Seven -- Chapter Eight -- Chapter Nine -- Chapter Ten -- Chapter Eleven -- Part III -- Chapter Twelve -- Chapter Thirteen -- Chapter Fourteen -- Chapter Fifteen -- Chapter Sixteen -- Chapter Seventeen -- Contributors. 330 $aOur ability to acquire a language - one of the most complex semiotic systems - is stunning. However, to describe and explain even a small fraction of this system and of this ability is a great challenge.This book brings together modified papers of seventeen university scholars from Belarus, Germany, Russia and Lithuania originally presented at an international conference held in Minsk, Belarus, in 2017, on different hidden and implicit aspects of language and the ways of disclosing and explicating them. Language is understood by them differently as a cognitive ability, a specific semiotic structure interwoven with culture, and a discourse. This book will be of great interest to a wide range of linguist-theoreticians, specialists in applied linguistics, and the general reader with an interest in understanding what exactly language is. 606 $aConnotation (Linguistics)$vCongresses 608 $aElectronic books. 615 0$aConnotation (Linguistics) 676 $a401.43 702 $aLiashchova$b Liudmila 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910480790003321 996 $aThe explicit and the implicit in language and speech$92484428 997 $aUNINA LEADER 01018nam0-2200337 --450 001 9910393260103321 005 20220916181416.0 010 $a978-88-6030-975-4 020 $aIT$b2018-10446 100 $a20200527d2018----kmuy0itay5050 ba 101 0 $aita 102 $aIT 105 $a 001yy 200 1 $a<>coscienza dell'Es$epsicoanalisi e neuroscienze$fMark Solms$ga cura di Andrea Clarici 210 $aMilano$cRaffaello Cortina$d2018 215 $aIX, 323 p.$d24 cm 225 1 $aPsichiatria psicoterapia neuroscienze 300 $aScelta di scritti 610 0 $aCervello$aRapporti [con la] Mente$aNeuroscienze 676 $a612.8233$v23 676 $a150.1 700 1$aSolms,$bMark$0213098 702 1$aClarici,$bAndrea 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910393260103321 952 $a150.2500 PPN 21$b2020/509$fFLFBC 952 $a150.2500 PPN 21 BIS$b2020/510$fFLFBC 959 $aFLFBC 996 $aCoscienza dell'Es$91743618 997 $aUNINA LEADER 05422nam 22007935 450 001 9910483838203321 005 20251226200021.0 010 $a3-540-47128-6 024 7 $a10.1007/11899402 035 $a(CKB)1000000000284056 035 $a(SSID)ssj0000321041 035 $a(PQKBManifestationID)11231147 035 $a(PQKBTitleCode)TC0000321041 035 $a(PQKBWorkID)10276814 035 $a(PQKB)11737929 035 $a(DE-He213)978-3-540-47128-8 035 $a(MiAaPQ)EBC3068556 035 $a(PPN)123139147 035 $a(EXLCZ)991000000000284056 100 $a20100301d2006 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAdvances in Web Mining and Web Usage Analysis $e6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004, Seattle, WA, USA, August 22-25, 2004, Revised Selected Papers /$fedited by Bamshad Mobasher, Olfa Nasraoui, Bing Liu, Brij Masand 205 $a1st ed. 2006. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2006. 215 $a1 online resource (X, 189 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3932 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-47127-8 320 $aIncludes bibliographical references and index. 327 $aWeb Usage Analysis and User Modeling -- Mining Temporally Changing Web Usage Graphs -- Improving the Web Usage Analysis Process: A UML Model of the ETL Process -- Web Personalization and Recommender Systems -- Mission-Based Navigational Behaviour Modeling for Web Recommender Systems -- Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors -- Collaborative Quality Filtering: Establishing Consensus or Recovering Ground Truth? -- Search Personalization -- Spying Out Accurate User Preferences for Search Engine Adaptation -- Using Hyperlink Features to Personalize Web Search -- Semantic Web Mining -- Discovering Links Between Lexical and Surface Features in Questions and Answers -- Integrating Web Conceptual Modeling and Web Usage Mining -- Boosting for Text Classification with Semantic Features -- Markov Blankets and Meta-heuristics Search: Sentiment Extraction from Unstructured Texts. 330 $aTheWebisaliveenvironmentthatmanagesanddrivesawidespectrumofapp- cations in which a user may interact with a company, a governmental authority, a non-governmental organization or other non-pro?t institution or other users. User preferences and expectations, together with usage patterns, form the basis for personalized, user-friendly and business-optimal services. Key Web business metrics enabled by proper data capture and processing are essential to run an e?ective business or service. Enabling technologies include data mining, sc- able warehousing and preprocessing, sequence discovery, real time processing, document classi?cation, user modeling and quality evaluation models for them. Recipient technologies required for user pro?ling and usage patterns include recommendation systems, Web analytics applications, and application servers, coupled with content management systems and fraud detectors. Furthermore, the inherent and increasing heterogeneity of the Web has - quired Web-based applications to more e?ectively integrate a variety of types of data across multiple channels and from di?erent sources. The development and application of Web mining techniques in the context of Web content, Web usage, and Web structure data has already resulted in dramatic improvements in a variety of Web applications, from search engines, Web agents, and content management systems, to Web analytics and personalization services. A focus on techniques and architectures for more e?ective integration and mining of c- tent, usage,and structure data from di?erent sourcesis likely to leadto the next generation of more useful and more intelligent applications. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3932 606 $aArtificial intelligence 606 $aComputer networks 606 $aDatabase management 606 $aInformation storage and retrieval systems 606 $aApplication software 606 $aComputers and civilization 606 $aArtificial Intelligence 606 $aComputer Communication Networks 606 $aDatabase Management 606 $aInformation Storage and Retrieval 606 $aComputer and Information Systems Applications 606 $aComputers and Society 615 0$aArtificial intelligence. 615 0$aComputer networks. 615 0$aDatabase management. 615 0$aInformation storage and retrieval systems. 615 0$aApplication software. 615 0$aComputers and civilization. 615 14$aArtificial Intelligence. 615 24$aComputer Communication Networks. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aComputer and Information Systems Applications. 615 24$aComputers and Society. 676 $a006.3 701 $aMobasher$b Bamshad$0899226 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483838203321 996 $aAdvances in Web mining and Web usage analysis$94198412 997 $aUNINA