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This project is a Chinese text segmentation library and tokenizer designed to split Chinese sentences into individual words. It serves as a natural language processing tool for splitting characters into words, tagging parts of speech, and extracting keywords using statistical analysis. The library distinguishes itself through support for custom dictionary configuration and vocabulary file management, allowing users to override default segmentation rules for domain-specific accuracy. It also includes a TF-IDF keyword extractor to identify significant words and core topics within documents. Th
Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others.
pkuseg-python is a Chinese word segmentation toolkit and natural language processing library. It provides specialized models for splitting Chinese text into words across various domains, including news, medical, and web content, and includes a tool for assigning grammatical parts of speech tags to segmented words. The library allows for the training of custom segmentation models using annotated datasets and supports the integration of user-defined dictionaries to ensure specialized terminology is recognized correctly. It employs a multi-threaded execution engine to process large volumes of Ch
a chinese segment base on crf
The main features of duanhongyi/genius are: Natural Language Processing, Word Segmentation Tools.
Projects with overlapping indexed features include: go-ego/gse — Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others. lancopku/pkuseg-python — pkuseg-python is a Chinese word segmentation toolkit and natural language processing library. It provides specialized… fangpenlin/loso — Chinese segmentation library. fxsjy/jieba — This project is a Chinese text segmentation library and tokenizer designed to split Chinese sentences into individual… abitdodgy/gibran — Gibran is an Elixir natural language processor, and a port of WordsCounted. 7compass/sentimental — Simple sentiment analysis with Ruby.
