Presenter : Jian-Ren Chen Authors : Sheng-Tun Li a,b,* , Fu-Ching Tsai a 2013 , KBS

1. A fuzzy conceptualization model for text mining with application in opinion polarity classification Presenter : Jian-Ren ChenAuthors : Sheng-Tun Lia,b,*, Fu-Ching Tsaia2013 , KBS

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

3. Motivation Most existing document classification algorithms are easily affected by ambiguous terms. The ability to disambiguate for a classifier is thus as important as the ability to classify accurately. - opinion polarity classification

4. Objectives • We propose a concept driven text classification approach based on Formal Concept Analysis (FCA) to train a classifier using concepts instead of documents, so as to reduce the inherent ambiguities. • We further utilize fuzzy formal concept analysis (FFCA) to take uncertain information into consideration.

5. Formal concept analysis Objects: {Review6,Review7} Attributes: {Phenomenal, Fantastic, Love} => formal concept negativeclass: ‘‘Awful’’ {Review2, Review3} neutral class: ‘‘Cover’’ {Review5} positiveclass: ‘‘Phenomenal’’, ‘‘Fantastic’’ and ‘‘Love’’ {Review1,Review4, Review6 and Review7}

6. Formal concept analysis positiveclass: {Review1,Review4, Review6, Review7} negativeclass: {Review2, Review3} neutral class: {Review5}

7. Methodology - Architecture

8. Methodology tf-idf: Inverted Conformity Frequency (ICF): Uniformity (Uni): tf-idf> 26 ICF < log(2) Uni > 0.2

9. Methodology

10. Methodology

11. Experiments -Data set and evaluation • Data set: • Reuter-21578 • movie review • e-book review • Evaluation

12. Experiments (parameters)

13. Experiments

14. Experiments(conceptualization)

15. Experiments

16. Experiments

17. Conclusions • FFCM successfully reduce the impact from textual ambiguity. • The results from the experiments show that FFCM outperforms other state-of-the-art algorithms for both Reuters-21578 and two opinion polarity collections.

18. Comments • Advantages • the formal concepts plays an important role • Disadvantage • αmay differ from variousdatasets • only focuses on single-class classification • Applications • text mining