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Cross-Disciplinary Advances in Applied Natural Language Processing

Book Description

Applied Natural Language Processing (ANLP) is interested in not only the creation of natural language processing approaches (i.e., tools, systems, algorithms, models, theories, and techniques), but it is also (and, arguably, more specifically) interested in how those approaches stack up against new problems, issues, identified knowledge gaps, or created data sets. Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches defines the role of ANLP within NLP, and alongside other disciplines such as linguistics, computer science, and cognitive science. The description also includes the categorization of current ANLP research, and examples of current research in ANLP. This book is a useful reference for teachers, students, and materials developers in fields spanning linguistics, computer science, and cognitive science.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
  5. Foreword
  6. Preface
    1. INTRODUCTION
    2. THE FIELD TRIUMVIRATE
    3. ORGANIZATION OF THE BOOK
    4. GOING FORWARD
  7. Acknowledgment
  8. Section 1:
    1. Chapter 1: Computational Semantics Requires Computation
      1. ABSTRACT
      2. INTRODUCTION
      3. REFERENCE AND COMPSEM
      4. THE ADVENT OF THE SEMANTIC WEB
      5. CONCLUSION
    2. Chapter 2: Natural Language Processing Tools
      1. ABSTRACT
      2. INTRODUCTION
      3. FUTURE RESEARCH DIRECTIONS
      4. CONCLUSION
      5. APPENDIX: ADDITIONAL RESOURCES
    3. Chapter 3: Information Extraction from Text and Beyond
      1. ABSTRACT
      2. INTRODUCTION
      3. 2. BACKGROUND AND PROBLEM DEFINITION
      4. 3. THE NEED TO LEARN FROM UNLABELED EXAMPLES
      5. 4. THE NEED TO AUTOMATICALLY LEARN EXTERNAL KNOWLEDGE
      6. 5. THE NEED FOR GENERIC INFORMATION EXTRACTION
      7. 6. FUTURE RESEARCH INTO COMPLEX EXTRACTIONS
      8. 7. THE BRIDGE TOWARDS TEXT UNDERSTANDING
      9. 8. CONCLUSION
    4. Chapter 4: Corpora and Concordancers
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. CONCLUSION
    5. Chapter 5: Lexical Challenges in the Intersection of Applied Linguistics and ANLP
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. CONSTRUCTS AND SIGNATURES
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    6. Chapter 6: The User-Language Paraphrase Corpus
      1. ABSTRACT
      2. THE NEED FOR ACCURATE USER-LANGUAGE EVALUATION
      3. THE SEVEN MAJOR PROBLEMS WITH EVALUATING USER-LANGUAGE
      4. COMPUTATIONAL APPROACHES TO EVALUATING USER-LANGUAGE IN ITSS
      5. PARAPHRASE DIMENSION
      6. HUMAN EVALUATIONS OF PROTOCOLS
      7. INTER-RATER AGREEMENT
      8. PERFORMANCE RESULTS
      9. CONCLUDING REMARKS
    7. Chapter 7: Amazon Mechanical Turk
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
    8. Chapter 8: Some Issues on Capturing the Meaning of Negated Statements
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. NEGATION IN NATURAL LANGUAGE
      5. SEMANTIC REPRESENTATION OF NEGATION
      6. AUTOMATIC DISCOVERY OF SCOPE AND FOCUS
      7. CONCLUSION
    9. Chapter 9: Cognitive Load Aspects of Text Processing
      1. Abstract
      2. INTRODUCTION
      3. THE ARCHITECTURE OF NATURAL INFORMATION PROCESSING SYSTEMS
      4. HUMAN COGNITIVE ARCHITECTURE
      5. COGNITIVE LOAD IN TEXT PROCESSING
      6. SOURCES OF EXTRANEOUS COGNITIVE LOAD
      7. PREVENTING COGNITIVE OVERLOAD
      8. ROLE OF PRIOR KNOWLEDGE IN COGNITIVE LOAD
      9. EXPERTISE REVERSAL EFFECT IN TEXT PROCESSING
      10. OPTIMIZING COGNITIVE LOAD
      11. FUTURE RESEARCH DIRECTIONS
      12. CONCLUSION
    10. Chapter 10: Understanding and Reasoning with Text
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SPECIFIC APPLICATIONS
      5. ISSUES, CONTROVERSIES, PROBLEMS
      6. CONCLUSION
  9. Section 2:
    1. Chapter 11: Guru
      1. ABSTRACT
      2. IDENTIFICATION
      3. INVESTIGATION
      4. RESOLUTION
      5. EXPERT HUMAN TUTORING
      6. KNOWLEDGE REPRESENTATION
      7. NATURAL LANGUAGE UNDERSTANDING
      8. NATURAL LANGUAGE GENERATION
      9. CONCLUSION
    2. Chapter 12: P-MATCH
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND PRIOR APPROACH
      4. P-MATCH
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    3. Chapter 13: Disambiguation and Filtering Methods in Using Web Knowledge for Coreference Resolution
      1. ABSTRACT
      2. INTRODUCTION
      3. RELATED WORK
      4. BASELINE
      5. USING WIKIPEDIA TO IMPROVE ALIASING
      6. USING YAGO TO EXTRACT SEMANTIC KNOWLEDGE
      7. EVALUATION AND ERROR ANALYSIS
      8. CONCLUSION
    4. Chapter 14: Newness and Givenness of Information
      1. ABSTRACT
      2. INTRODUCTION
      3. THEORETICAL ACCOUNTS OF THE NEW/GIVEN DIMENSION
      4. METHOD
      5. RESULTS
      6. DISCUSSION
      7. APPENDIX: SAMPLE TEXT
    5. Chapter 15: Improving Spoken Dialogue Understanding Using Phonetic Mixture Models
      1. ABSTRACT
      2. INTRODUCTION
      3. METHOD
      4. RESULTS
      5. DISCUSSION
    6. Chapter 16: Mining and Visualizing the Narration Tree of Hadiths (Prophetic Traditions)
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. PROPOSED SYSTEM
      5. EVALUATION AND RESULTS
      6. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    7. Chapter 17: Combinatory Categorial Grammar for Computer-Assisted Language Learning
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. RESULTS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    8. Chapter 18: Fairy Tales and ESL Texts
      1. ABSTRACT
      2. INTRODUCION
      3. RESULTS
      4. DISCUSSION
    9. Chapter 19: Text-Based Affect Detection in Intelligent Tutors
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. BRIEF INTRODUCTION TO Coh-Metrix
      5. TUTORIAL DIALOGUE CORPUS ANNOTATED FOR LEARNER AFFECT
      6. RESULTS AND DISCUSSION
      7. FUTURE DIRECTIONS
      8. CONCLUSION
    10. Chapter 20: Multiple Influences on the Use of English Spatial Prepositions
      1. ABSTRACT
      2. INTRODUCTION
      3. EXPERIMENTS WITH AND
      4. EXPERIMENT 1
      5. EXPERIMENT 2
      6. GENERAL DISCUSSION
    11. Chapter 21: Evaluating Semantic Metrics on Tasks of Concept Similarity
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. EXPERIMENTAL SETUP
      5. RESULTS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
    12. Chapter 22: Extracting Commonsense Knowledge Using Concepts Properties
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. APPROACH
      5. BASIC METARULE: OBJECT PROPERTIES IMPLY COMMONSENSE
      6. EXTENSIONS
      7. RESTRICTIONS AND EXCEPTIONS
      8. IMPLEMENTATION
      9. RESULTS AND EVALUATION
      10. FUTURE RESEARCH DIRECTIONS
      11. CONCLUSION
    13. Chapter 23: Co-Occurrence-Based Error Correction Approach to Word Segmentation
      1. ABSTRACT
      2. INTRODUCTION
      3. RELEVANT ISSUES
      4. MAIN FOCUS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  10. Compilation of References
  11. About the Contributors