Sentiment analysis can be fine tuned using custom dictionaries, for example, sentiment polarity changed or additional sentiments extracted. In my blog I will explain how to archive something different - link sentiment to correct topic.
I run Voice of Customer text analysis against some reviews with standard EXTRACTION_CORE_VOICEOFCUSTOMER configuration. What I found is that "microwave safe bowl" was incorrectly interpreted as WeakPositiveSentiment.
"safe" sentiment was linked to incorrect topic e.g. "a microwave" instead of "bowl". I do not care about a bowl as such and the sentiment just screw up my analysis. Excluding "safe" adjective from custom dictionary looks like a simple solution, but solves one problem and creates another (what if I need to extract "microwave is safe" WeakPositive Sentiment). The right solution is to define a new neutral sentiment "microwave safe" adjective in custom dictionary. This way "safe" sentiment is linked to the right topic e.g. "bowl".
Then reference custom dictionary in custom configuration
and finally recreate text index
If I query against $TA table again, I will see that sentiments are correctly extracted
You can try described demo in your system. Import TA_DEMO.tgz transport (rename TA_DEMO.tgz.txt to TA_DEMO.tgz first). ta_demo package will be created
and finally execute install.sql script. The latter will create REVIEW table with data, grants proper authorization to TA_DEMO schema and creates text index with standard EXTRACTION_CORE_VOICEOFCUSTOMER configuration.
