Sentiment Extraction Functions - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Published
September 2017
Language
English (United States)
Last Update
2018-04-17
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uce1497542673292.ditamap
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B700-1022
lifecycle
previous
Product Category
Software

Sentiment extraction is the process of inferring user sentiment (positive, negative, or neutral) from text (typically call center logs, forums, and social media).

The sentiment extraction functions are:

  • TrainSentimentExtractor, which trains a model—takes training documents and outputs a maximum entropy classification model
  • ExtractSentiment, which uses either the classification model or a dictionary model to extract the sentiment of each input document or sentence; that is, to output predictions
  • EvaluateSentimentExtractor, which uses test data to evaluate the precision and recall of the predictions


The sentiment extraction functions support English, Simplified Chinese, and Traditional Chinese text.