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Automatic Keyphrase Extraction by Bridging Vocabulary Gap

Automatic Keyphrase Extraction by Bridging Vocabulary Gap. Presenter : Wu, Min-Cong Authors: Zhiyuan Liu, Xinxiong Chen, Yabin Zheng , Maosong Sun 2011, FCCNLL. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation.

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Automatic Keyphrase Extraction by Bridging Vocabulary Gap

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  1. Automatic Keyphrase Extraction by Bridging Vocabulary Gap Presenter: Wu, Min-Cong Authors: Zhiyuan Liu, Xinxiong Chen,YabinZheng, Maosong Sun2011, FCCNLL 1

  2. Outlines • Motivation • Objectives • Methodology • Experiments • Conclusions • Comments 2

  3. Motivation • Most methods extract keyphrases according to their statistical properties in the given document. This makes a large vocabulary gap between a document and its keyphrases. 3

  4. Objectives • We use word alignment models in statistical machine translation to learn translation probabilities between the words in documents and the words in keyphrases. 4

  5. Methodology- Bridging Vocabulary Gap Using WAM 5

  6. Methodology- Preparing Translation Pairs 6

  7. Methodology- Title-based Pairs 7

  8. Methodology- Summary-based Pairs 8

  9. Methodology- Training Translation Models translation pair connection 9

  10. Methodology- Keyphrase Extraction Noun phrase normalized TFIDF scores 10

  11. Experiment Dataset: 5-fold cross validation 11

  12. Experiment-Evaluation on Keyphrase Extraction Performance Comparison and Analysis 12

  13. Experiment-Influences of Parameters to TPR Influence of Parameters When Titles/Summaries Are Unavailable 13

  14. Experiment-Beyond Extraction: Keyphrase Generation 14

  15. Conclusions • We use IBM Model-1 to bridge the vocabulary gap between the two languages for keyphrasegeneration. 15

  16. Comments • Advantages • Our method can capture the semantic relations between words in documents and keyphrases. • Applications • Keyphraseextraction. 16

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