## Tags
- Part of:
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## Main resources
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- <iframe src="https://en.wikipedia.org/wiki/Natural_language_processing" allow="fullscreen" allowfullscreen="" style="height:100%;width:100%; aspect-ratio: 16 / 5; "></iframe>
## Landscapes
- [[Transformer]]
- [[GPT4]], [[Gemini]]
## Written by AI (may include factually incorrect information)
- Natural Language Processing (NLP) is a field at the intersection of [[Computer science]], [[Artificial Intelligence]], and [[Linguistics]], focused on the interactions between [[Computing|computers]] and human [[Language|languages]]. It encompasses a wide range of techniques and approaches for processing and understanding natural language. Here's a comprehensive list of various branches and topics within NLP:
### 1. Text and Speech Processing
- Text Normalization
- Tokenization
- Stemming and Lemmatization
- Part-of-Speech Tagging
- Speech Recognition
- Speech Synthesis
### 2. Syntax and Parsing
- Syntactic Analysis
- Dependency Parsing
- Constituency Parsing
- Grammar Induction
### 3. Semantic Analysis
- Word Sense Disambiguation
- Semantic Role Labeling
- Named Entity Recognition
- Coreference Resolution
- Semantic Parsing
### 4. Pragmatics and Discourse
- Dialogue Systems and Chatbots
- Discourse Analysis
- Anaphora and Coreference Resolution
- Pragmatic Analysis for Intent and Implicature
### 5. Machine Translation
- Statistical Machine Translation
- Neural Machine Translation
- Rule-Based Machine Translation
- Post-Editing and Quality Estimation
### 6. Information Retrieval
- Search Engines
- Document Indexing and Retrieval
- Query Expansion
- Relevance Feedback
### 7. Information Extraction
- Entity Extraction and Linking
- Relation Extraction
- Event Extraction
- Fact Checking and Verification
### 8. Sentiment Analysis and Opinion Mining
- Sentiment Classification
- Aspect-Based Sentiment Analysis
- Emotion Detection
- Opinion Summarization
### 9. Text Generation and Summarization
- Automatic Text Summarization
- Language Generation Models
- Narrative Generation
- Data-to-Text Generation
### 10. Question Answering Systems
- Factoid Question Answering
- Open-Domain Question Answering
- Reading Comprehension Models
- Visual Question Answering
### 11. Natural Language Understanding
- Intent Classification
- Slot Filling
- Contextual Understanding
- Conversational AI
### 12. Natural Language Generation
- Template-Based Generation
- Neural Text Generation
- Data-to-Text Systems
- Content Creation and Storytelling
### 13. Topic Modeling and Text Clustering
- Latent Dirichlet Allocation (LDA)
- Non-Negative Matrix Factorization
- Text Clustering Techniques
### 14. Word and Phrase Embeddings
- Word2Vec
- GloVe
- FastText
- Contextual Embeddings (e.g., BERT, GPT)
### 15. Deep Learning in NLP
- Recurrent Neural Networks (RNNs)
- Convolutional Neural Networks (CNNs)
- [[Transformer]] Models
- Transfer Learning in NLP
### 16. Multimodal NLP
- Image and Video Captioning
- Multimodal Sentiment Analysis
- Visual-Textual Content Analysis
### 17. Evaluation Metrics and Techniques
- BLEU, ROUGE for Machine Translation and Summarization
- Precision, Recall, F1-Score for Classification Tasks
### 18. Computational Sociolinguistics
- Language Variation and Change
- Computational Analysis of Social Media
- Digital Humanities
### 19. NLP for Low-Resource Languages
- Cross-Lingual and Multilingual NLP
- Language Adaptation Techniques
- Resource Creation for Under-Resourced Languages
### 20. Ethical and Societal Aspects of NLP
- Bias and Fairness in NLP Models
- Ethical Considerations in Language Technologies
- Privacy and Security in Text and Speech Processing
NLP is a rapidly evolving field with diverse applications, including chatbots, machine translation, sentiment analysis, and information extraction. It continues to be shaped by advancements in machine learning, deep learning, and data availability.