Working with Text: Tools, Techniques and Approaches for Text Mining

What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining.

Introduces text analysis and text mining toolsProvides a comprehensive overview of costs and benefitsIntroduces the topic, making it accessible to a general audience in a variety of fields, including examples from biology, chemistry, sociology, and criminology

Chapter 1: Working with Text

Chapter 2: A Day at Work (with Text): A Brief Introduction

Chapter 3: If You Find Yourself in a Hole, Stop Digging: Legal and Ethical Issues of Text/Data Mining in Research

Chapter 4: Responsible Content Mining

Chapter 5: Text Mining for Semantic Search in Europe PubMed Central Labs

Chapter 6: Extracting Information from Social Media with GATE

Chapter 7: Newton: Building an Authority-Driven Company Tagging and Resolution System

Chapter 8: Automatic Language Identification

Chapter 9: User-Driven Text Mining of Historical Text

Chapter 10: Automatic Text Indexing with SKOS Vocabularies in HIVE

Chapter 11: The PIMMS Project and Natural Language Processing for Climate Science: Extending the ChemicalTagger Natural Language Processing Tool with Climate Science Controlled Vocabularies

Chapter 12: Building Better Mousetraps: A Linguist in NLP

Chapter 13: Raúl Garreta, Co-founder of Tryolabs.com, Tells Emma Tonkin About the Journey from Software Engineering Graduate to Startup Entrepreneur