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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 Key Insight: Imposing market structure assumption ◦ Different type of information extraction Amazon review text
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Opinion = (orientation, polarity) Review Texts Orientation Profile Rating ∞ m k
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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 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 Performance
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