Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	August 2025
Genre:	Schulbücher
	AI-assisted scraping / AJAX Handling / API Data Extraction / Cloud Scraping / CSS Selectors / Data Mining / Data Mining and Knowledge Discovery / Dynamic Websites / Headless Browsers / HTML Parsing / HTTP Requests / JavaScript Scraping / JSON Processing / Methodology of Data Collection and Processing / Pagination Handling / r programming / reproducible research / Restful apis / Sozialforschung und -statistik / tidyverse / Web Crawler Design / Web Mining / Web Scraping / Wirtschaftswissenschaft, Finanzen, Betriebswirtschaft und Management / Wissensbasierte Systeme, Expertensysteme / XML Parsing mehr...
ISBN:	9783031966378
EAN-Code:	9783031966378
Verlag:	Springer International Publishing
Einband:	Kartoniert
Sprache:	English
Dimensionen:	H 235 mm / B 155 mm / D
Seiten:	251
Illustration:	XXI, 251 p. 34 illus., 18 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book is devoted to the art and science of web mining — showing how the world's largest information source can be turned into structured, research-ready data. Drawing on many years of teaching graduate courses on Web Mining and on numerous large-scale research projects in web mining contexts, the author provides clear explanations of key web technologies combined with hands-on R tutorials that work in the real world — and keep working as the web evolves. Through the book, readers will learn how to - scrape static and dynamic/JavaScript-heavy websites - use web APIs for structured data extraction from web sources - build fault-tolerant crawlers and cloud-based scraping pipelines - navigate CAPTCHAs, rate limits, and authentication hurdles - integrate AI-driven tools to speed up every stage of the workflow - apply ethical, legal, and scientific guidelines to their web mining activities Part I explains why web data matters and leads the reader through a first "hello-scrape" in R while introducing HTML, HTTP, and CSS. Part II explores how the modern web works and shows, step by step, how to move from scraping static pages to collecting data from APIs and JavaScript-driven sites. Part III focuses on scaling up: building reliable crawlers, dealing with log-ins and CAPTCHAs, using cloud resources, and adding AI helpers. Part IV looks at ethical, legal, and research standards, offering checklists and case studies, enabling the reader to make responsible choices. Together, these parts give a clear path from small experiments to large-scale projects. This valuable guide is written for a wide readership — from graduate students taking their first steps in data science to seasoned researchers and analysts in economics, social science, business, and public policy. It will be a lasting reference for anyone with an interest in extracting insight from the web — whether working in academia, industry, or the public sector.