rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Working with text
    sub title: tools, techniques and approaches for text mining
  name:
    name part: Tonkin, Emma
    role:
      role term: editor.
  name:
    name part: Tourte, Gregory J. L.
    role:
      role term: editor.
  name:
    name part: ScienceDirect (Online service)
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: mau
    date issued: 2016
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource
  abstract: 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.
  table of contents: 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.
  table of contents: 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.
  table of contents: 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.
  table of contents: 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.
  table of contents: 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.
  note: edited by Emma L. Tonkin, Gregory J.L. Tourte.
  note: Includes bibliographical references and index.
  subject:
    topic: Data mining
  subject:
    topic: Data Mining
  subject:
    topic: Exploration de données (Informatique)
  subject:
    topic: COMPUTERS
    topic: Databases
    topic: Data Mining
  subject:
    topic: COMPUTERS
    topic: General
  subject:
    topic: Data mining
  classification: QA76.9.D343
  classification: 006.312
  related item:
    title info:
      title: Working with Text : Tools, Techniques and Approaches for Text Mining
    name:
      name part: Tonkin, Emma.
    origin info:
      publisher: OXford : Elsevier Science, ©2016
  related item:
    title info:
      title: Chandos information professional series
  identifier: 9781780634302
  identifier: 1780634307
  identifier: 1843347490
  identifier: 9781843347491
  identifier: 940325 MIL
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: UKMGB
    record creation date: 140716
    record change date: 20260326211333.8
    record identifier: in00005757200
    language of cataloging:
      language term: eng