Lecture Notes in Computer Science 5549 1st Edition by Kenneth Church, Alexander Gelbukh ISBN 3642003818 9783642003813

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ISBN 10: 3642003818
ISBN 13: 9783642003813
Author: Kenneth Church, Alexander Gelbukh

Lecture Notes in Computer Science 5549 1st Edition Table of contents:

Part I: Natural Language Processing Fundamentals

2. Introduction to Text Mining and Information Retrieval

   • Basics of Text Mining: Techniques and Applications
   • Information Retrieval Models and Evaluation Metrics
   • The Role of Search Engines in NLP

3. Language Models: Theory and Implementation

   • N-Grams and Statistical Language Models
   • Deep Learning and Neural Language Models
   • Evaluating Language Model Performance

4. Syntax and Parsing Techniques in NLP

   • Syntax Representation: Constituency vs. Dependency Parsing
   • Statistical and Rule-Based Parsing Methods
   • Advances in Syntax Parsing for Complex Languages

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Part II: Semantic Analysis and Knowledge Representation

5. Word Sense Disambiguation and Semantic Parsing

   • Techniques for Disambiguating Word Meanings
   • The Role of Context in Semantic Interpretation
   • Applications in Machine Translation and Information Retrieval

6. Named Entity Recognition and Relation Extraction

   • Identifying Entities in Text
   • Relation Extraction from Structured and Unstructured Data
   • Evaluation Methods for Named Entity Recognition Systems

7. Knowledge Graphs and Ontologies in NLP

   • Building and Using Knowledge Graphs
   • The Role of Ontologies in Natural Language Understanding
   • Applications of Knowledge Representation in NLP

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Part III: Machine Learning and NLP

8. Supervised and Unsupervised Learning in Language Processing

   • Supervised Approaches: Training and Evaluation
   • Unsupervised Approaches: Clustering and Topic Modeling
   • Hybrid Models for Better Language Understanding

9. Deep Learning for Natural Language Processing

   • Recurrent Neural Networks (RNNs) and Long Short-Term Memory Networks (LSTMs)
   • Transformers and Attention Mechanisms
   • BERT, GPT, and Other Pre-trained Models

10. Transfer Learning in NLP: Approaches and Challenges

    • Fine-Tuning Pre-trained Models for Specific NLP Tasks
    • Cross-Lingual Transfer Learning
    • Challenges in Domain Adaptation for NLP Models

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Part IV: Applications of NLP

11. Sentiment Analysis and Opinion Mining

    • Techniques for Extracting Sentiment from Text
    • Applications in Social Media and Customer Feedback Analysis
    • Sentiment Analysis Challenges in Multi-language Contexts

12. Machine Translation: From Rule-Based to Neural Networks

    • Evolution of Machine Translation Systems
    • Statistical and Neural Approaches to Machine Translation
    • Evaluation Metrics and Quality Assessment

13. Text Summarization: Techniques and Tools

    • Extractive vs. Abstractive Summarization
    • Deep Learning for Text Summarization
    • Applications of Text Summarization in News and Social Media

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Part V: Advanced Topics in NLP

14. Multimodal Language Processing

    • Combining Text, Image, and Speech Data
    • Applications in Human-Computer Interaction
    • Challenges and Future Directions in Multimodal NLP

15. Ethics and Bias in Natural Language Processing

    • Identifying Bias in Language Models
    • Ethical Considerations in NLP Applications
    • Addressing Fairness and Transparency in NLP Systems

16. The Future of NLP: Challenges and Emerging Trends

    • Open Problems in NLP Research
    • The Role of Multilinguality in NLP
    • Innovations in NLP for Healthcare, Law, and Education

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