Please enable JavaScript.
Coggle requires JavaScript to display documents.
Natural Language Processing - Coggle Diagram
Natural Language Processing
What is Natural Language?
Natural language refers to any language that has developed naturally among humans through use and social interaction, such as English, Spanish, or Mandarin. It is used for everyday communication and is characterized by its complexity and variability.
Formal and Natural Language
Formal Language
A formal language consists of a set of strings of symbols that are constructed using specific rules and used for precise purposes like mathematics, computer science, and logic.
Structured and follows specific syntactical rules
Unambiguous and consistent in interpretation
Designed for specialized applications like programming or formal proofs
Natural Language
Natural language is used by humans for everyday communication, evolving naturally over time without predefined rules.
Rich and flexible with varied syntax and semantics
Prone to ambiguity and context-dependence
Evolved for efficient and expressive human interaction
Syntax
Syntax is the set of rules, principles, and processes that govern the structure of sentences in a language. It determines how words combine to form grammatical sentences.
Focuses on sentence structure and word order
Essential for understanding and generating coherent language
Involves parsing sentences to understand their hierarchical structure
Natural Language Processing (NLP)
Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language. It involves enabling computers to understand, interpret, and generate human language.
Applications of NLP
Text classification: Sentiment analysis, spam detection
Machine translation: Translating text from one language to another
Speech recognition: Converting spoken language into text
Chatbots and virtual assistants: Automated customer service
Information extraction: Identifying structured information from unstructured text
Summarization: Condensing long documents into summaries
Machine Learning
Machine learning is a subset of artificial intelligence that involves training algorithms to recognize patterns and make decisions based on data. It enables systems to improve their performance over time without explicit programming.
Supervised, unsupervised, and reinforcement learning
Uses statistical techniques to give computers the ability to learn from data
Applications include predictive modeling, classification, and clustering
Lexicon
A lexicon is the complete set of words in a language, including their meanings, forms, and usage. It serves as a dictionary that provides the vocabulary necessary for language processing.
History of NLP
1950s: Alan Turing's "Computing Machinery and Intelligence," introduction of the Turing Test
1960s: Development of early NLP systems like ELIZA, a simple chatbot
1970s: Introduction of more sophisticated parsing techniques and grammars
1980s: Shift towards machine learning approaches with statistical models
1990s: Rise of probabilistic models and corpus-based methods
2000s: Growth of NLP applications and the advent of deep learning
Web Links
https://www.oracle.com/in/artificial-intelligence/what-is-natural-language-processing/#:~:text=Natural%20language%20processing%20(NLP)%20is,natural%20language%20text%20or%20voice
.
https://www.techtarget.com/searchenterpriseai/definition/natural-language-processing-NLP
https://www.spiceworks.com/tech/artificial-intelligence/articles/what-is-ml/#:~:text=Machine%20learning%20(ML)%20is%20defined,predictions%20with%20minimal%20human%20intervention
.
N-gram
An N-gram is a contiguous sequence of n items from a given sample of text or speech. In NLP, N-grams are used for various tasks, including language modeling and text prediction.
Can be unigrams (single words), bigrams (pairs of words), trigrams (triplets), etc.
Useful in predicting the next item in a sequence and in understanding text patterns
Helps in building models for machine translation, speech recognition, and text generation