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Pro, Con, and Affinity Tagging of Product Reviews

Pro, Con, and Affinity Tagging of Product Reviews. Todd Sullivan. The Task. Given a product review, what are the pros, cons, and affinities chosen by the reviewer?. Example. Another Example. Systems. Bag of words Naïve Bayes (baseline) Maximum Entropy Classifier

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Pro, Con, and Affinity Tagging of Product Reviews

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  1. Pro, Con, and Affinity Tagging of Product Reviews Todd Sullivan

  2. The Task • Given a product review, what are the pros, cons, and affinities chosen by the reviewer?

  3. Example

  4. Another Example

  5. Systems • Bag of words Naïve Bayes (baseline) • Maximum Entropy Classifier • Combinatorial Tag Optimization • Preprocessing Methods • Lowercasing, removing punctuation, stop words list, vocabulary restriction, etc. • Maximum Entropy Feature Selection • Combinatorial Tag OptimizationWeights Selection

  6. Results on the Pro “Compact”

  7. Overall Maxent Results

  8. Multi-Tag OptimizationImprovement on Affinities

  9. Future Work • Human study of tagging performance • More advanced textual features using dependency trees / phrase structure trees • Better sentence boundary detection and tokenization (Balie did not work too well) • Focus on feature development for cons and affinities (spent all of our time on pros)

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