LEADER 03243 am 2200613 n 450 001 9910495802903321 005 20240104030441.0 010 $a2-7574-2751-2 010 $a2-7574-0511-X 024 7 $a10.4000/books.septentrion.67614 035 $a(CKB)4100000005467228 035 $a(FrMaCLE)OB-septentrion-67614 035 $a(PPN)25107093X 035 $a(EXLCZ)994100000005467228 100 $a20201123j|||||||| ||| 0 101 0 $afre 135 $auu||||||m|||| 200 00$aAlbert Camus au Quotidien$fAndré Benhaïm, Aymeric Glacet 210 $aVilleneuve d'Ascq$cPresses universitaires du Septentrion$d2020 215 $a1 online resource (206 p.) 311 $a2-7574-0446-6 327 $tAvant-propos /$rAndre? Benhai?m, Aymeric Glacet --$tLa lec?on de Tipasa /$rMichel Onfray --$tCamus et ses histoires de concierge /$rAymeric Glacet --$tLes aliments dans l'oeuvre romanesque de Camus /$rGerald Prince --$tEsthe?tique de l'interruption : Camus entre quotidien et histoire /$rDavid R. Ellison --$tQuand le jeune Camus ouvre les yeux sur le quotidien /$rAgne?s Spiquel --$tLa mise?re au quotidien : Camus et la Kabylie /$rE?ve Morsi --$tE?cologies de l'appartenance chez Camus /$rDebarati Sanyal --$tEntre rhe?torique et ontologie : le quotidien dans La chute d'Albert Camus /$rNicolas L'Hermitte --$tExpe?rience et connaissance du quotidien dans l'oeuvre de Camus /$rEdward J. Hughes --$tPoe?tique de l'insignifiance : les anecdotes d'Albert Camus /$rAndre? Benhai?m. 330 $aInvoquant « la révolte au jour le jour », Albert Camus cherchait dans la vie le bonheur dont il avait fait la quête ultime de l?homme. Le présent volume explore dans l??uvre et l?imaginaire de Camus l?importance du quotidien, l?aura du banal, l?étendue du journalier. On y rappelle que, par l?intermédiaire du petit fait vrai ou du pilotis cher à Stendhal, du fait divers ou de l?objet anodin, le quotidien inspire à l?écrivain sa réponse à la brutalité de l?histoire et à l?absurdité du monde. Ce travail collectif se propose ainsi de porter un regard nouveau sur une ?uvre à célébrer au quotidien. 517 $aALBERT CAMUS AU QUOTIDIEN 606 $aLiterary Reviews 606 $aquotidien 606 $abanal 606 $aécrivain 606 $a?uvre littéraire 606 $alittérature française 615 4$aLiterary Reviews 615 4$aquotidien 615 4$abanal 615 4$aécrivain 615 4$a?uvre littéraire 615 4$alittérature française 686 $aIH 24081$2rvk 700 $aBenhaïm$b André$0734694 701 $aEllison$b David R$01031195 701 $aGlacet$b Aymeric$01239618 701 $aHughes$b Edward J$01454446 701 $aL?Hermitte$b Nicolas$01454447 701 $aMorisi$b Ève$01454448 701 $aOnfray$b Michel$0472123 701 $aPrince$b Gerald$0142977 701 $aSanyal$b Debarati$01283463 701 $aSpiquel$b Agnès$0387018 701 $aBenhaïm$b André$0734694 701 $aGlacet$b Aymeric$01239618 801 0$bFR-FrMaCLE 906 $aBOOK 912 $a9910495802903321 996 $aAlbert Camus au Quotidien$93656904 997 $aUNINA LEADER 04006nam 22006855 450 001 9910629299603321 005 20251113195012.0 010 $a9783031165528 010 $a3031165527 024 7 $a10.1007/978-3-031-16552-8 035 $a(MiAaPQ)EBC7131894 035 $a(Au-PeEL)EBL7131894 035 $a(CKB)25280436100041 035 $a(PPN)266356230 035 $a(OCoLC)1493049502 035 $a(DE-He213)978-3-031-16552-8 035 $a(EXLCZ)9925280436100041 100 $a20221103d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aQuestion Answering over Text and Knowledge Base /$fby Saeedeh Momtazi, Zahra Abbasiantaeb 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (208 pages) 225 1 $aComputer Science Series 311 08$a9783031165511 311 08$a3031165519 320 $aIncludes bibliographical references. 330 $aThis book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning. After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9. This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge. 410 0$aComputer Science Series 606 $aInformation storage and retrieval systems 606 $aExpert systems (Computer science) 606 $aMachine learning 606 $aNatural language processing (Computer science) 606 $aInformation Storage and Retrieval 606 $aKnowledge Based Systems 606 $aMachine Learning 606 $aNatural Language Processing (NLP) 615 0$aInformation storage and retrieval systems. 615 0$aExpert systems (Computer science) 615 0$aMachine learning. 615 0$aNatural language processing (Computer science) 615 14$aInformation Storage and Retrieval. 615 24$aKnowledge Based Systems. 615 24$aMachine Learning. 615 24$aNatural Language Processing (NLP). 676 $a006.3 676 $a006.3 700 $aMomtazi$b Saeedeh$01266141 702 $aAbbasiantaeb$b Zahra 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910629299603321 996 $aQuestion answering over text and knowledge base$93059068 997 $aUNINA