1.0 - 8.00 - SentimentExtractor Example 5: Dictionary Table Instead of Model File - Teradata Vantage

Teradata® Vantage Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.0
8.00
Release Date
May 2019
Content Type
Programming Reference
Publication ID
B700-4003-098K
Language
English (United States)

This example uses a dictionary table, sentiment_word, instead of a model file.

Input

sentiment_word
word opinion
screwed 2
excellent 2
incredible 2
terrific 2
outstanding 2
fun 1
love 1
nice 1
big 0
update 0
constant 0
small 0
mistake -1
difficulty -1
disappointed -1
not tolerate -1
stuck -1
terrible -2
crap -2

SQL Call

SELECT * FROM SentimentExtractor (
  ON sentiment_extract_input PARTITION BY ANY
  ON sentiment_word AS dict DIMENSION
  USING
  TextColumn ('review')
  AnalysisType ('document')
  Accumulate ('id', 'product')
) AS dt ORDER BY id;

Output

id product out_polarity out_strength out_sentiment_words
1 camera POS 2 excellent 2, excellent 2. In total, positive score:4 negative score:0
2 office suite POS 2 terrific 2, terrific 2. In total, positive score:4 negative score:0
3 camera POS 2 nice 1, small 0, love 1. In total, positive score:2 negative score:0
4 gps POS 2 outstanding 2, incredible 2. In total, positive score:4 negative score:0
5 gps POS 2 nice 1, big 0. In total, positive score:1 negative score:0
6 gps NEU 0 update 0. In total, positive score:0 negative score:0
7 gps POS 2 screwed 2. In total, positive score:2 negative score:0
8 camera NEG 2 stuck -1, difficulty -1. In total, positive score:0 negative score:-2
9 television NEG 2 crap -2, big 0. In total, positive score:0 negative score:-2
10 camera NEG 2 not tolerate -1, constant 0. In total, positive score:0 negative score:-1