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Outlines

High Relevance Keyword Extraction facility for Bayesian text classification on different domains of varying characteristic. Presenter : Min-Cong Wu Authors : Lam Hong Lee, Dino Isa, Wou Onn Choo , Wen Yeen Chue 2012.ESA. Outlines. Motivation Objectives Methodology Experiments

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Outlines

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  1. High Relevance Keyword Extraction facility for Bayesian text classification on different domains of varying characteristic Presenter : Min-Cong WuAuthors : Lam Hong Lee, Dino Isa, WouOnnChoo, Wen YeenChue2012.ESA

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

  3. Motivation • Bayesian classification as compared to other classification approaches is its ability and simplicity in handling raw text data directly • As a trade-off to its simplicity, Bayesian classification has been reported as one of the poorest-performing classification approaches.

  4. Objectives • By use to HRKE facility enhance the accuracy of Bayesian classifier without sacrificing the low cost.

  5. Methodology – Block diagram

  6. Methodology – Bayesian Classifier

  7. Methodology – TF-IDF method TF*IDF • TF-IDF = • TF(Term Frequency)，IDF(Inverse Document Frequency) • N=This word contains the number of document in dataset • Example:

  8. Methodology – HRKE facility • The degree of relevance of keywords in the classification task can be adjusted by setting a threshold, m/n.

  9. Experiment-the basic flat ranking multivariate

  10. Experiment - Featured Articles dataset

  11. Experiment - Vehicles dataset

  12. Experiment - Mathematics dataset

  13. Experiment - 20-Newsgroups dataset

  14. Experiment - Summary

  15. Conclusions • HRKE facility is achieved through applying unique feature selection method based on the occurrence of keywords in documents from a specified category, and compares the occurrence of those keywords in each of the competing categories.

  16. Comments • Advantages Improve Bayesian classification performance and can maintain low cost. • Applications - Feature selection

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