Modern Text Mining Framework for R

as.lda_c | Converts document-term matrix sparse matrix to 'lda_c' format |

BNS | BNS |

check_analogy_accuracy | Checks accuracy of word embeddings on the analogy task |

coherence | Coherence metrics for topic models |

Collocations | Collocations model. |

combine_vocabularies | Combines multiple vocabularies into one |

create_dtm | Document-term matrix construction |

create_tcm | Term-co-occurence matrix construction |

create_vocabulary | Creates a vocabulary of unique terms |

distances | Pairwise Distance Matrix Computation |

GlobalVectors | Creates Global Vectors word-embeddings model. |

glove | Fit a GloVe word-embedded model |

ifiles | Creates iterator over text files from the disk |

itoken | Iterators (and parallel iterators) over input objects |

LatentDirichletAllocation | Creates Latent Dirichlet Allocation model. |

LatentSemanticAnalysis | Latent Semantic Analysis model |

movie_review | IMDB movie reviews |

normalize | Matrix normalization |

perplexity | Perplexity of a topic model |

prepare_analogy_questions | Prepares list of analogy questions |

prune_vocabulary | Prune vocabulary |

reexports | Objects exported from other packages |

RelaxedWordMoversDistance | Creates model which can be used for calculation of "relaxed... |

similarities | Pairwise Similarity Matrix Computation |

split_into | Split a vector for parallel processing |

text2vec | text2vec |

TfIdf | TfIdf |

tokenizers | Simple tokenization functions for string splitting |

vectorizers | Vocabulary and hash vectorizers |

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