LEADER 01156nas 2200385- 450 001 9910717601303321 005 20241014213015.0 011 $a2788-2233 035 $a(OCoLC)1379729938 035 $a(CKB)2560000000235531 035 $a(CONSER)--2024224798 035 $a(DE-599)ZDB3175900-2 035 $a(EXLCZ)992560000000235531 100 $a20170808a20089999 --- - 101 0 $aeng 135 $aur|n||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aAmerican & British studies annual 210 1$a[Paradubice], Czech Republic$cFaculty of Arts and Humanities, University of Pardubice. 215 $a1 online resource 300 $aRefereed/Peer-reviewed. 300 $aRefereed/Peer-reviewed 311 08$a1803-6058 517 3 $aAmerican and British studies annual 517 1 $aABSA 531 1 $aAm. Br. Stud. Annu. 607 $aGreat Britain$xCivilization$vPeriodicals 607 $aAmerica$xCivilization$vPeriodicals 676 $a300 906 $aJOURNAL 912 $a9910717601303321 996 $aAmerican & British studies annual$94205823 997 $aUNINA LEADER 04427nam 22008055 450 001 9910983377403321 005 20250214115229.0 010 $a9783031766312 010 $a3031766318 024 7 $a10.1007/978-3-031-76631-2 035 $a(MiAaPQ)EBC31908849 035 $a(Au-PeEL)EBL31908849 035 $a(CKB)37527870800041 035 $a(DE-He213)978-3-031-76631-2 035 $a(OCoLC)1500765733 035 $a(EXLCZ)9937527870800041 100 $a20250214d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNatural Language Analytics with Generative Large-Language Models $eA Practical Approach with Ollama and Open-Source LLMs /$fby Francisco S. Marcondes, Adelino Gala, Renata Magalhães, Fernando Perez de Britto, Dalila Durães, Paulo Novais 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (117 pages) 225 1 $aSpringerBriefs in Computer Science,$x2191-5776 311 08$a9783031766305 311 08$a303176630X 327 $aIntroduction -- Natural Language Analytics -- Using Ollama -- Generative Prompt Engineering -- Case Study: LLM-based Anxiety Climate Index -- Conclusion. 330 $aThis book explores the application of generative Large Language Models (LLMs) for extracting and analyzing data from natural language artefacts. Unlike traditional uses of LLMs, such as translation and summarization, this book focuses on utilizing these models to convert unstructured text into data that can be processed through the data science pipeline to generate actionable insights. The content is designed for professionals in diverse fields including cognitive science, linguistics, management, and information systems. It combines insights from both industry and academia to provide a comprehensive understanding of how LLMs can be effectively used for natural language analytics (NLA). The book details practical methodologies for implementing LLMs locally using open-source tools, ensuring data privacy and feasibility without the need for expensive infrastructure. Key topics include interpretant, mindset and cultural analysis, emphasizing the use of LLMs to derive soft data?qualitative information crucial for nuanced decision-making. The text also outlines the technical aspects of LLMs, including their architecture, token embeddings, and the differences between encoder-based and decoder-based models. By providing a case study and practical examples, the authors show how LLMs can be used to meet various analytical needs, making this book a valuable resource for anyone looking to integrate advanced natural language processing techniques into their data analysis workflows. 410 0$aSpringerBriefs in Computer Science,$x2191-5776 606 $aNatural language processing (Computer science) 606 $aArtificial intelligence$xData processing 606 $aArtificial intelligence 606 $aBusiness$xData processing 606 $aComputational linguistics 606 $aMachine learning 606 $aNatural Language Processing (NLP) 606 $aData Science 606 $aArtificial Intelligence 606 $aBusiness Analytics 606 $aComputational Linguistics 606 $aMachine Learning 615 0$aNatural language processing (Computer science) 615 0$aArtificial intelligence$xData processing. 615 0$aArtificial intelligence. 615 0$aBusiness$xData processing. 615 0$aComputational linguistics. 615 0$aMachine learning. 615 14$aNatural Language Processing (NLP). 615 24$aData Science. 615 24$aArtificial Intelligence. 615 24$aBusiness Analytics. 615 24$aComputational Linguistics. 615 24$aMachine Learning. 676 $a006.35 700 $aMarcondes$b Francisco S$01784298 701 $aGala$b Adelino$01784299 701 $aMagalhães$b Renata$01784300 701 $aPerez de Britto$b Fernando$01784301 701 $aDurães$b Dalila$01372655 701 $aNovais$b Paulo$0762363 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983377403321 996 $aNatural Language Analytics with Generative Large-Language Models$94315975 997 $aUNINA