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Action Rules Mining Triggered by Micro-actions and Its Application in Education

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Frontiers in Computer Education

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 133))

Abstract

Action rules describe possible transitions of objects from one state to another with respect to a distinguished attribute. Early research on action rule discovery usually required the extraction of classification rules before constructing any action rule. Newest algorithms discover action rules directly from a decision system. This paper gives a new approach for generating action rules by incorporating a pruning step through micro-actions. The notion of Micro-actions is introduced. They are nodes in a higher-level knowledge, which are linked with atomic terms showing changes within classification attributes. New influence matrix is presented and used to show the cascading effect of actions modeled as action rules. Moreover, an application of the proposed approach in education is demonstrated.

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References

  1. Agrawal, R., Srikant, R.: Fast algorithm for mining association rules. In: Proceeding of the Twentieth International Conference on VLDB, pp. 487–499 (1994)

    Google Scholar 

  2. Dardzínska, A., Rás, Z.: Extracting rules from incomplete decision systems. In: Foundations and Novel Approaches in Data Mining. SCI, vol. 9, pp. 143–154. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Fensel, D.: Ontologies: a silver bullet for knowledge management and electronic commerce. Springer, Heidelberg (1998)

    Google Scholar 

  4. Greco, S., Matarazzo, B., Pappalardo, N., Slowínski, R.: Measuring expected effects of interventions based on decision rules. J. Exp. Theor. Artif. Intell. 17(1-2), 103–118 (2005)

    Article  MATH  Google Scholar 

  5. Grzymala-Busse, J.: A new version of the rule induction system LERS. Fundamenta Informaticae 31(1), 27–39 (1997)

    MATH  Google Scholar 

  6. He, Z., Xu, X., Deng, S., Ma, R.: Mining action rules from scratch. Expert Systems with Applications 29(3), 691–699 (2005)

    Article  Google Scholar 

  7. Im, S., Raś, Z.W.: Action rule extraction from a decision table: ARED. In: An, A., Matwin, S., Raś, Z.W., Ślęzak, D. (eds.) ISMIS 2008 . LNCS (LNAI), vol. 4994, pp. 160–168. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Pawlak, Z.: Information systems - theoretical foundations. Information Systems Journal 6, 205–218 (1981)

    Article  MATH  Google Scholar 

  9. Qiao, Y., Zhong, K., Wang, H.-A., Li, X.: Developing event-condition-action rules in real-time active database. In: Proceedings of the 2007 ACM Symposium on Applied Computing, pp. 511–516. ACM, New York (2007)

    Chapter  Google Scholar 

  10. Raś, Z.W., Dardzińska, A.: Action Rules Discovery, a New Simplified Strategy. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 445–453. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Raś, Z.W., Dardzińska, A.: Action Rules Discovery Without Pre-Existing Classification Rules. In: Chan, C.-C., Grzymala-Busse, J.W., Ziarko, W.P. (eds.) RSCTC 2008. LNCS (LNAI), vol. 5306, pp. 181–190. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  12. Raś, Z.W., Dardzińska, A., Tsay, L.-S., Wasyluk, H.: Association Action Rules. In: Proceedings of IEEE/ICDM Workshop on Mining Complex Data (MCD 2008), Pisa, Italy. IEEE Computer Society (2008)

    Google Scholar 

  13. Raś, Z.W., Wieczorkowska, A.A.: Action-rules: How to increase profit of a company. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 587–592. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  14. Raś, Z.W., Tzacheva, A., Tsay, L.-S., Gürdal, O.: Mining for interesting action rules. In: Proceedings of IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2005), pp. 187–193. Compiegne University of Technology, France (2005)

    Google Scholar 

  15. Raś, Z.W., Wyrzykowska, E., Wasyluk, H.: ARAS: Action Rules Discovery Based on Agglomerative Strategy. In: Raś, Z.W., Tsumoto, S., Zighed, D.A. (eds.) MCD 2007. LNCS (LNAI), vol. 4944, pp. 196–208. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  16. Tsay, L.-S., Raś, Z.W.: Action Rules Discovery System DEAR_3. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 483–492. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  17. Tzacheva, A., Raś, Z.W.: Constraint Based Action Rule Discovery with Single Classification Rules. In: An, A., Stefanowski, J., Ramanna, S., Butz, C.J., Pedrycz, W., Wang, G. (eds.) RSFDGrC 2007. LNCS (LNAI), vol. 4482, pp. 322–329. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  18. Wang, K., Jiang, Y., Tuzhilin, A.: Mining Actionable Patterns by Role Models. In: Proceedings of the 22nd International Conference on Data Engineering, pp. 16–25. IEEE Computer Society (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Jinan Lixia Experimental Primary School, Jinan, 250010, China

    Yuan Liu

  2. Jinan Yanshan School, Jinan, 250100, China

    Xuemei Zhao

  3. Jigang Baoshan School, Jinan, 250013, China

    Yumei Zhang

Authors
  1. Yuan Liu
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  2. Xuemei Zhao
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  3. Yumei Zhang
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Corresponding author

Correspondence to Yuan Liu .

Editor information

Editors and Affiliations

  1. South China Normal University, Guangzhou, 510631, China, People's Republic

    Sabo Sambath

  2. South China Normal University, Guangzhou, 510631, China, People's Republic

    Egui Zhu

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Liu, Y., Zhao, X., Zhang, Y. (2012). Action Rules Mining Triggered by Micro-actions and Its Application in Education. In: Sambath, S., Zhu, E. (eds) Frontiers in Computer Education. Advances in Intelligent and Soft Computing, vol 133. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27552-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-27552-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27551-7

  • Online ISBN: 978-3-642-27552-4

  • eBook Packages: EngineeringEngineering (R0)

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