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Natural Language Processing (NLP): An article on understanding NLP natural language processing technology, NLP applications in daily life, deepening understanding through graph guidance, NLP corpus, NLP open-source tools
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Classification Column: Natural Language Processing (NLP) Computer/Artificial Intelligence High Quality Article Label: Natural Language Processing Artificial Intelligence
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1. Natural Language Processing NLP
1.1 NLP Chinese English control (double copy)
1.2 Related Articles
2. NLP Corpus
2.1 NLP Corpus Enumeration
2.2 Related Articles
3. NLP Open Source Tools
3.1 NLP Open Source Tool List
3.2 Related Articles
4. Natural language text classification model code
5. Graph leader NLP
6. Application of NLP in daily life
1. Natural Language Processing NLP
1.1 NLP Chinese English control (double copy)
NLP Chinese English control (double copy)
Natural Language Processing (NLP) is a branch of computer science and artificial intelligence aimed at enabling computers to understand, parse, generate, and manipulate human language. It combines knowledge from multiple disciplines such as computer science, linguistics, and mathematical statistics, providing powerful text analysis and language processing tools for people. NLP is widely used, such as machine translation, sentiment analysis, automatic question answering, speech recognition, text classification, and information extraction.
English (1) Natural Language Processing (NLP) is a branch of computer science and artistic intelligence aimed at enabling computers to understand, parse, generate, and manipulate human language It combines knowledge from multiple disciplines such as computer science, linguistics, and mathematical statistics, providing powerful text analysis and language processing tools for people NLP is widely used, such as machine translation, sensitive analysis, automatic question answering, speech recognition, text classification, and information extraction
Chinese (2) NLP represents natural language processing. It is a branch of artificial intelligence that focuses on enabling computers to understand, interpret, and generate human language. This includes teaching computers to recognize speech patterns, grammar, grammar, and context, as well as responding appropriately to human language input. NLP has various applications, such as chat robots, speech recognition, language translation, sentiment analysis, etc. NLP is becoming increasingly important in areas such as customer service, healthcare, education, and marketing.
English (2) NLP stands for Natural Language Processing It is a branch of artistic intelligence that focuses on enabling computers to understand, interpret, and generate human language This investments teaching computers to recognize speech patterns, syntax, grammar, and context, as well as to respond appropriately to human language input NLP has various applications such as chatbots, speech recognition, language translation, timely analysis, and more NLP is becoming increasingly important in fields such as customer service, healthcare, education, and marketing, among others
1.2 Related Articles
Natural Language Processing (NLP) Technology
Icon default. png? T=N7T8 https://blog.csdn.net/SYC20110120/article/details/132029884
2. NLP Corpus
2.1 NLP Corpus Enumeration
NLP Corpus Enumeration
1. Commonly used English corpora: Penn Treebank, GigaWord, Brown Corpus, Reuters Corpus, Web Text, etc
2. Chinese Corpus: People's Daily Corpus, Xinhua News Agency Corpus, Chinese Commonly Used Words (CCG) Corpus, Fudan University Chinese Text Classification Corpus, etc
3. Social media corpus: Twitter corpus, Facebook corpus, Reddit corpus, etc
4. Multilingual corpus: Europarl, Tatoeba, Wikipedia, OPUS, etc
5. Medical Corpus: MEDLINE, PubMed, etc
6. Legal Corpus: American Legal Document Corpus, British Legal Document Corpus, etc
7. Technology corpus: Google Books Ngrams, Google News Dataset, etc
8. Speech recognition corpus: TIMIT, CSJ, etc
2.2 Related Articles
Chinese Academy of Sciences Corpus
Icon default. png? T=N7T8 https://blog.csdn.net/SYC20110120/article/details/132722058
3. NLP Open Source Tools
3.1 NLP Open Source Tool List
NLP Open Source Tool List
1. NLTK (Natural Language Toolkit): A commonly used NLP tool library in Python, which includes multiple functions such as word segmentation, part of speech tagging, named entity recognition, text classification, and grammar analysis
2. SpaCy: Another NLP tool library in Python, with fast speed, rich functionality, and support for multilingual processing
Stanford NLP: The NLP toolset developed by Stanford University, which includes multiple modules such as word segmentation, part of speech tagging, syntactic analysis, and named entity recognition
4. OpenNLP: Java NLP toolset developed by Apache, including multiple modules such as word segmentation, named entity recognition, and syntax analysis
5. Gensim: A natural language processing library in Python, used for text similarity calculation, document topic model, and other applications
6. CoreNLP: Part of the NLP toolset developed by Stanford University, which supports multilingual processing and includes multiple modules such as word segmentation, part of speech tagging, syntactic analysis, and sentiment analysis
7. FastText: Facebook's open-source NLP tool that can perform tasks such as word vector training, text classification, and text clustering
8. AllenNLP: An NLP tool library based on PyTorch implementation, providing multiple pre trained models, including tasks such as text classification and reading comprehension
3.2 Related Articles
Introduction to NLP Open Source Tools
Icon default. png? T=N7T8 https://blog.csdn.net/SYC20110120/article/details/132646555
4. Natural language text classification model code
Code for Natural Language Text Classification Model
Icon default. png? T=N7T8 https://blog.csdn.net/SYC20110120/article/details/132080301
5. Graph leader NLP
6. Application of NLP in daily life
The application of NLP in daily life
1. Intelligent assistants: Intelligent assistants such as Siri, Alexa, and Google Assistant are all built based on NLP technology. They can understand human language and answer questions or perform tasks
2. Speech recognition: NLP technology is used to recognize what we say and convert it into editable text. Speech recognition can be used for voice assistants, voice search, voice control, and more
3. Machine translation: NLP technology can be used to translate one language into another. This technology is very important for cross-border exchanges such as trade and tourism
4. Information extraction: NLP can extract key information from a large amount of text, such as extracting key events from news reports or extracting terms and details from commercial contracts
5. Emotional analysis: NLP technology can be used to evaluate the emotional color of a large amount of data, such as analyzing the emotional color of comments posted on social media
6. Question answering system: NLP technology can be used to build automatic question answering systems. For example, in the field of customer service, users can communicate with robots through natural language to obtain answers and solve problems
7. Natural language generation: NLP technology can be used to automatically generate articles, abstracts, text messages, etc. This technology has applications in fields such as news reporting, advertising, and social media
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