pythainlp.word_vector

The word_vector contains functions that makes use of a pre-trained vector public data. The pythainlp.word_vector module is a valuable resource for working with pre-trained word vectors. These word vectors are trained on large corpora and can be used for various natural language processing tasks, such as word similarity, document similarity, and more.

Dependencies

Installation of numpy and gensim is required.

Before using this module, you need to ensure that the numpy and gensim libraries are installed in your environment. These libraries are essential for loading and working with the pre-trained word vectors.

Modules

References

• [Omer Levy and Yoav Goldberg (2014). Linguistic Regularities in Sparse and Explicit Word Representations](https://www.aclweb.org/anthology/W14-1618/) This reference points to the work by Omer Levy and Yoav Goldberg, which discusses linguistic regularities in word representations. It underlines the theoretical foundation of word vectors and their applications in NLP.

This enhanced documentation provides a more detailed and organized overview of the pythainlp.word_vector module, making it a valuable resource for NLP practitioners and researchers working with pre-trained word vectors in the Thai language.