slides - The Stanford NLP

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Jiho Han
Ronny (Dowon) Ko
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Objective: automatically generate the summary of
review extracting the strength/weakness of the
product
Use NLP techniques to predict ratings
◦ Similar to sentimental analysis
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Key Insight: Imposing market structure assumption
◦ Different type of information extraction
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Amazon review text
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Opinion = (orientation, polarity)
Review Texts
Orientation
Profile
∞
m
k
Rating
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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
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Extract market profiling and pricing kernel
Update word polarity
Repeat until no more improvement
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Extract the words that have significant effect
on rating (in terms of maximizing entropy)
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Initial word polarity
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Change in polarity
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Performance
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