New L2 normalization in TF-IDF document aligner #252
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Before, we were not taking into account any infrequent or very frequent n-gram for the L2 normalization in the document score calculation. Now we follow these rules: - If the n-gram is in `df`, we use the normal TF-IDF. - If the n-gram is not in `df`, calculate the TF-IDF assuming a document frequency of 1. - If the n-gram is not in `df`, but it is a frequent one (as defined by the parameter `max_count`), then do not use the calculated TF-IDF and ignore the n-gram.
Before, we were not taking into account any infrequent or very frequent n-gram for the L2 normalization in the document score calculation. Now we follow these rules: - If the n-gram is in `df`, we use the normal TF-IDF. - If the n-gram is not in `df`, calculate the TF-IDF assuming a document frequency of 1. - If the n-gram is not in `df`, but it is a frequent one (as defined by the parameter `max_count`), then do not use the calculated TF-IDF and ignore the n-gram.
…xtor into docalign_new_score
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Before, we were not taking into account any infrequent or very frequent n-gram for the L2 normalization in the document score calculation. Now we follow these rules:
— If the n-gram is in
df, we use the normal TF-IDF.— If the n-gram is not in
df, calculate the TF-IDF assuming a document frequency of 1.— If the n-gram is not in
df, but it is a frequent one (as defined by the parametermax_count), then do not use the calculated TF-IDF and ignore the n-gram.