http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
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.
Front Cover; Working with Text: Tools, Techniques and Approaches for Text Mining; Copyright; Contents; Contributors; Preface; Acknowledgements; Chapter 1: Working with Text; 1.1. Introduction: Portraits of the Past; 1.2. The Reading Robot; 1.3. From Data to Text Mining; 1.4. Definitions of Text Mining; 1.5. Exploring the Disciplinary Neighbourhood; 1.6. Prerequisites for Text Mining; 1.7. Learning Minecraft: What Makes a Text Miner?; 1.8. Contemporary Attitudes to Text Mining; 1.9. Conclusions; References; Chapter 2: A Day at Work (with Text): A Brief Introduction; 2.1. Introduction.
2.2. Encouraging an Interest in Text Mining2.3. Legal and Ethical Aspects of Text Mining; 2.3.1. Activities; 2.3.2. Selecting or Compiling a Data Set or Corpus; 2.3.3. Building a Data Set; 2.4. Manual Annotation: Preparing for Evaluation; 2.4.1. Avoidance of Overfitting; 2.4.2. Characterising the Problem; 2.4.3. Managing User Expectations; 2.5. Common Text Mining Tasks; 2.6. Basic Corpus Analysis; 2.6.1. Evaluating Frequency of Word and Term Use; 2.6.2. Identifying Characteristic Words or Terms; 2.7. Preprocessing a Text; 2.8. Extracting Features from a Text; 2.9. Information Extraction.
2.9.1. Terminology Extraction2.9.2. Named Entity Recognition (NER); 2.9.3. Entity Disambiguation; 2.9.4. Relationship Extraction and Coreference Resolution; 2.9.5. Fact Extraction; 2.9.6. Temporal Information Extraction; 2.9.7. Automated Geotagging or Geoindexing of Text; 2.10. Applications of Indexing and Metadata Extraction; 2.11. Extraction of Subjective Views; 2.11.1. Opinion Mining; 2.11.2. Sentiment Analysis; 2.12. Build, Customise or Apply? Choosing an Appropriate Implementation; 2.13. Evaluation; 2.13.1. Evaluating Accuracy: Precision, Recall and F-measure.
2.13.2. Process Cost in Resources, Time and Processing Resources2.13.3. Fit with User Requirements and Expectations; 2.13.4. Contextualisation of Results; 2.14. The Role of Visualisation in Text Mining; 2.15. Visualisation Tools and Frameworks; 2.16. Conclusions; References; Chapter 3: If You Find Yourself in a Hole, Stop Digging: Legal and Ethical Issues of Text/Data Mining in Research; 3.1. Introduction; 3.1.1. The Relationship Between Law and Ethics; 3.1.2. Law, Technology and Change; 3.2. Key Legal Issues in Data Mining; 3.2.1. Data as Property.
3.2.1.1. Data Mining and Utilitarian Copyright Perspectives3.2.2. Data as Personally Identifying Information (PII); 3.2.2.1. Text/Data Mining and Accountability; 3.2.3. Primum non Nocere: Some Thoughts on False Positives, Patternicity and Liability; 3.2.3.1. The Road to Hell May Be Paved With Risky (but Often Necessary) Assumptions; 3.2.3.2. You Call it a ``Failure Mode, ́́ I Call it ``Possible Grounds for Legal Action;́́ 3.3. Ethics; 3.3.1. A Research Ethics Framework for Data/Text Mining; 3.4. Conclusions: Working on the Borders of Law and Ethics; References.
edited by Emma L. Tonkin, Gregory J.L. Tourte.
Includes bibliographical references and index.
Working with Text : Tools, Techniques and Approaches for Text Mining