Jiho Han
Ronny (Dowon) Ko
Objective: automatically generate the summary of
review extracting the strength/weakness of the
product
Use NLP techniques to predict ratings
◦ Similar to sentimental analysis
Key Insight: Imposing market structure assumption
◦ Different type of information extraction
Amazon review text
Opinion = (orientation, polarity)
Review Texts
Orientation
Profile
∞
m
k
Rating
Parsing – through Stanford NLP syntax parser
Initializing orientation and polarity
◦ Selecting polarity words through decision tree (Max-Ent)
◦ Orientation using N-gram (uni + bi)
◦ Use wordnet when testing
Extract market profiling and pricing kernel
Update word polarity
Repeat until no more improvement
Extract the words that have significant effect
on rating (in terms of maximizing entropy)
Initial word polarity
Change in polarity
Performance
0
