LEADER 02410nam 2200457 450 001 9910830901603321 005 20191108133001.0 010 $a1-119-67104-3 010 $a1-119-67116-7 010 $a1-119-50729-4 035 $a(CKB)4100000009526198 035 $a(MiAaPQ)EBC5946038 035 $a(CaSebORM)9781786303035 035 $a(EXLCZ)994100000009526198 100 $a20191108d2019 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArgument mining $elinguistic foundations /$fMathilde Janier, Patrick Saint-Dizier 205 $a1st edition 210 1$aLondon, England ;$aHoboken, New Jersey :$cIste :$cWiley,$d[2019] 210 4$dİ2019 215 $a1 online resource (207 pages) 311 $a1-78630-303-5 330 $aThis book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner. 606 $aInformation retrieval 606 $aNatural language processing (Computer science) 615 0$aInformation retrieval. 615 0$aNatural language processing (Computer science) 676 $a025.524 700 $aJanier$b Mathilde$01636041 702 $aSaint-Dizier$b Patrick 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830901603321 996 $aArgument mining$93977131 997 $aUNINA