Word Embedding

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An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. The install folder contains the 'PATENTS' file. An example how to use 'fastTextR' can be found in the 'README' file.

Word2Vec

Java implementation of GloVe word embedding and document embedding

It offers functions for splitting, parsing, tokenizing and creating a vocabulary for big text data files. Moreover, it includes functions for building a document-term matrix and extracting information from those (term-associations, most frequent terms). It also embodies functions for calculating token statistics (collocations, look-up tables, string dissimilarities) and functions to work with sparse matrices. Lastly, it includes functions for Word Vector Representations (i.e. 'GloVe', 'fasttext') and ...

JFastText is a Java interface for fastText, a library for efficient learning of word representations and sentence classification.

This is a helper project for the usage of word embeddings. It is able to read pretrained embeddings from a word2vec file and offers direct access via the Deeplearning4j API or a web server that offers the embeddings via an HTTP interface.

Elasticsearch Word2Vec Plugin

JFastText is a Java interface for fastText, a library for efficient learning of word representations and sentence classification.

A Clojure wrapper for the Medallia word2vecJava implementation

Word2Vec Java Port