A new rule pruning text categorisation method

2010 7th International Multi-Conference on Systems, Signals and Devices, SSD-10

Volumn , Issue , 2010, Pages

  Thabtah, Fadi ^a   Hadi, Wa'el ^a   Abu Mansour, Hussein ^b   McCluskey, L ^b  

^a PHILADELPHIA UNIVERSITY   (Jordan)

^b UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

Author keywords

Classification; Data mining; Rule pruning; Text categorisation

Indexed keywords

ASSOCIATIVE CLASSIFICATION; CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION APPROACH; CLASSIFICATION TIME; PRUNING METHODS; PRUNING TECHNIQUES; RULE PRUNING; TEXT CATEGORISATION;

ASSOCIATIVE PROCESSING; CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DECISION TREES; TEXT PROCESSING;

DATA MINING;

EID: 78149235227     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SSD.2010.5585572     Document Type: Conference Paper

References (18)

1. Antonie M. and Zaïane O. (2004). An associative classifier based on positive and negative rules. Proceedings of the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (pp. 64-69), Paris, France.
2. Baralis E., Chiusano S. and Garza P. (2008). A Lazy Approach to Associative Classification. IEEE Trans. Knowl. Data Eng. 20(2): 156-171.
3. Baralis E., Chiusano S. and Garza P. (2004). On support thresholds in associative classification. Proceedings of the 2004 ACM Symposium on Applied Computing, (pp. 5 53-5 58). Nicosia, Cyprus.
4. Cohen W. (1995). Fast effective rule induction. Proceedings of the 12th International Conference on Machine Learning, (pp. 115-123). CA, USA.
5. Kundu G., Islam M., Munir S. and Bari M. (2008). ACN: An Associative Classifier with Negative Rules, Computational Science and Engineering, vol. 0, no. 0, (pp. 369-375), 11th IEEE International Conference on Computational Science and Engineering.
6. Lewis D. (1998). Reuters 21578 text categorisation test collection.http://www.daviddlewis.com/resources/testcollections/reuters21578.
7. Li B., Li H., Wu M. and Li P. (2008). Multi-label Classification based on Association Rules with Application to Scene Classification, icycs, (pp.36-41), 2008 The 9th International Conference for Young Computer Scientists.
8. Li W., Han J. and Pei J. (2001). CMAR: Accurate and efficient classification based on multiple-class association rule. Proceedings of the ICDM'01, (pp. 369-376). San Jose, CA.
9. Liu B., Hsu W. and Ma Y. (1998). Integrating classification and association rule mining. Proceedings of the KDD, (pp. 80-86). New York, NY.
10. Liu B., Ma Y., Wong, C-K. and Yu. P. (2003). Scoring the data using association rules. Applied Intelligence, 18(2003): 119-135.
11. Niu Q., Xia S. and Zhang L. (2009). Association Classification Based on Compactness of Rules, wkdd, (pp.245-247), Second International Workshop on Knowledge Discovery and Data Mining.
12. Quinlan J. (1998). Data mining tools See5 and C5.0. Technical Report, RuleQuest Research.
13. Quinlan J. and Cameron-Jones R. (1993). FOIL: A midterm report. Proceedings of the European Conference on Machine Learning, (pp. 3-20), Vienna, Austria.
14. Snedecor W. and Cochran W. (1989). Statistical Methods, Eighth Edition, Iowa State University Press.
15. Thabtah, F., Cowling, P., and Peng, Y. (2005) MCAR: Multi-class classification based on association rule approach. Proceeding of the 3rd IEEE International Conference on Computer Systems and Applications (pp. 1-7).Cairo, Egypt.
16. Thabtah, F., Cowling, P., and Peng, Y. (2004) MMAC: A new multi-class, multi-label associative classification approach. Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM '04), (pp. 217-224). Brighton, UK. (Nominated for the Best paper award).
17. Xu X., Han G. and Min H. (2004). A novel algorithm for associative classification of images blocks. Proceedings of the fourth IEEE International Conference on Computer and Information Technology, (pp. 46-51). Lian, Shiguo, China.
18. Yin X. and Han J. (2003). CPAR: Classification based on predictive association rule. Proceedings of the SDM (pp. 369-376). San Francisco, CA.