class PragmaticScorer extends Serializable
Scorer is a rule based implementation inspired on http://fjavieralba.com/basic-sentiment-analysis-with-python.html Its strategy is to tag words by a dictionary in a sentence context, and later identify such context to get amplifiers
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- new PragmaticScorer(sentimentDict: Map[String, String], POSITIVE_VALUE: Double = 1.0, NEGATIVE_VALUE: Double = -1.0, INCREMENT_MULTIPLIER: Double = 2.0, DECREMENT_MULTIPLIER: Double = -2.0, REVERT_MULTIPLIER: Double = -1.0)
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def
score(tokenizedSentences: Array[TokenizedSentence]): Double
scores lowercased words by their headers within a sentence context.
scores lowercased words by their headers within a sentence context. Sets the tag for every word
- tokenizedSentences
POS tagged sentence. POS tags are not really useful in this implementation for now.
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