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Automatic Snippet Generation for Music Reviews

Automatic Snippet Generation for Music Reviews. Chris Anderson Edward Segel Dan Wiesenthal. Problem. Movies. Music. ...but tons of online music criticism. Solution.

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Automatic Snippet Generation for Music Reviews

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  1. Automatic Snippet Generation for Music Reviews Chris Anderson Edward Segel Dan Wiesenthal

  2. Problem Movies Music ...but tons of online music criticism.

  3. Solution We focus on snippet generation in the domain of music reviews—that is, how do you choose a snippet from a music review that best captures the opinion of the reviewer?  

  4. Data training us original test

  5. Methodology • Score sentences using a scorer • tf-idf • Stopwords, Rare Terms • Naïve Bayes and MaxEnt • Features: • Linguistic: album name, “in conclusion”, “this album”, verbs in present tense • Positional: last sentence of review and/or paragraph • Sentiment • SentiWordNet: positivity, negativity, objectivity • Summed and averaged

  6. Evaluation • Random sentence baseline • Last / second to last / first sentence baseline • Hand-labeled test set • Bake off grading

  7. Results

  8. Results

  9. Results

  10. Results

  11. Conclusion / Future Work • Great data -> New summarization corpus • Test against other review sites • Hand weighted features worked better than learned features • Improve learning algorithms • Single sentence output produces pretty good summaries • Join sentences together grammatically and semantically

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