Idézet: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.

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.

Idézet:A kódrészlet megtekintéséhez be kell jelentkezned, vagy nincs jogosultságod a tartalom megtekintéséhez.