Embedding/Chinese-Word-Vectors
Chinese Word Vectors
This project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It serves as a library of linguistic representations and an NLP vector dataset designed to improve the accuracy of semantic and morphological analysis in text models.
The collection provides corpus-specific representations and utilizes n-gram co-occurrence modeling to capture diverse linguistic patterns. It includes a hybrid of dense-sparse vectors to balance computational efficiency and semantic precision.
The project covers semantic vector search and the development of Chinese natural language processing pipelines. It also includes tools for text embedding evaluation, utilizing analogy-based quality tests to measure morphological and semantic accuracy.
Features
- Chinese - Provides various pre-trained vector sets trained on different Chinese corpora to capture diverse linguistic patterns.
- Chinese NLP Libraries - Offers pre-trained embeddings specifically designed to improve semantic understanding for Chinese text NLP pipelines.
- Chinese Word Embedding Collections - Provides a set of pre-trained dense and sparse word vectors trained on diverse Chinese corpora.
- N-Gram Co-occurrence Models - Captures semantic relationships by analyzing the frequency of adjacent word fragments and character sequences during training.
- Pre-trained Vector Repositories - Maintains a collection of dense and sparse word embeddings derived from large-scale diverse Chinese text corpora.
- Hybrid Sparse-Dense Embeddings - Implements a hybrid of dense semantic vectors and sparse keyword-based vectors for balanced efficiency and precision.
- Pre-trained Vector Libraries - Provides a collection of linguistic representations used to improve the accuracy of semantic and morphological analysis.
- Word Embedding Datasets - Provides access to word embedding datasets trained on diverse corpora for NLP tasks.
- Embedding - Evaluates vector performance using specialized toolkits and datasets focused on morphological and semantic analogies.
- Analogy Solvers - Provides tools to solve morphological and semantic word relationship puzzles via vector arithmetic.
- Vector Search - Enables finding words or phrases with similar meanings using high-dimensional vector distance.
- Corpus-Specific Vectorizations - Generates distinct vector spaces based on the specific linguistic characteristics of different training data sources.
- Natural Language Processing - Listed in the “Natural Language Processing” section of the FunNLP awesome list.
- Pretrained Models and Embeddings - Large collection of pretrained Chinese word embeddings.
- Research and Datasets - Large-scale pre-trained word embeddings for Chinese NLP tasks.
- Corpus and Datasets - Collection of pre-trained Chinese word embeddings.
- Natural Language Corpora - Pre-trained word vector representations for Chinese.
