pysummarization.similarityfilter package

Submodules

pysummarization.similarityfilter.dice module

class pysummarization.similarityfilter.dice.Dice[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the Dice coefficient.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

pysummarization.similarityfilter.encoder_decoder_cosine module

class pysummarization.similarityfilter.encoder_decoder_cosine.EncoderDecoderCosine(document, tokenizable_doc=None, hidden_neuron_count=200, epochs=100, batch_size=100, learning_rate=1e-05, learning_attenuate_rate=0.1, attenuate_epoch=50, bptt_tau=8, weight_limit=0.5, dropout_rate=0.5, test_size_rate=0.3, debug_mode=False)[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the so-called Cosine similarity of Tf-Idf vectors.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

pysummarization.similarityfilter.jaccard module

class pysummarization.similarityfilter.jaccard.Jaccard[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the Jaccard coefficient.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

pysummarization.similarityfilter.simpson module

class pysummarization.similarityfilter.simpson.Simpson[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the Simpson coefficient.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

pysummarization.similarityfilter.tanimoto module

class pysummarization.similarityfilter.tanimoto.Tanimoto[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the Tanimoto coefficient.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

pysummarization.similarityfilter.tfidf_cosine module

class pysummarization.similarityfilter.tfidf_cosine.TfIdfCosine[source]

Bases: pysummarization.similarity_filter.SimilarityFilter

Concrete class for filtering mutually similar sentences.

calculate(token_list_x, token_list_y)[source]

Calculate similarity with the so-called Cosine similarity of Tf-Idf vectors.

Concrete method.

Parameters:
  • token_list_x – [token, token, token, …]
  • token_list_y – [token, token, token, …]
Returns:

Similarity.

Module contents