Skip to main content
SpringerLink
Log in
Book cover

International Workshop on Machine Learning and Data Mining in Pattern Recognition

MLDM 2013: Machine Learning and Data Mining in Pattern Recognition pp 390–404Cite as

Discovering Frequent Itemsets on Uncertain Data: A Systematic Review

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7988))

Abstract

In this paper, we describe the development of a systematic review about the topic “Discovering Frequent Itemsets on Uncertain Data”. To the best of our knowledge, this work seems to be the first systematic review addressing the topic. We show the whole process executed and its findings. Initially we define a rigorous protocol to lead the process. In the first phase, we create a systematic mapping of the area. In addition, from the complete reading of each article, a panorama of this area is presented. We reveal the search engines that most publicize this topic and which publishing types, authors and research institutions are involved in these papers. Moreover we identify the algorithms and the classes of these algorithms most compared over the years, how are made these comparisons, as well as their availabilities. Therefore this systematic review becomes a rich material for understanding this knowledge area.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aggarwal, C., et al.: Frequent Pattern Mining With Uncertain Data. In: 15th ACM SIGKDD, Paris (2009)

    Google Scholar 

  2. Aggarwal, C.: Managing and Mining Uncertain Data. Springer, USA (2009)

    Book  MATH  Google Scholar 

  3. Agrawal, R., Imielinski, T., Swami, A.: Mining Association Rules between Sets of Items in Large Databases. In: ACM SIGKDD (1993)

    Google Scholar 

  4. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules in Large Databases. In: VLDB (1994)

    Google Scholar 

  5. Bernecker, T., et al.: Probabilistic frequent itemset mining in uncertain databases. In: 15th ACM SIGKDD (2009)

    Google Scholar 

  6. Bhadoria, R.S., Kumar, R., Dixit, M.: Analysis on probabilistic and binary datasets through frequent itemset mining. In: WICT 2011 (2011)

    Google Scholar 

  7. Bhatt, C.: Kankanhalli M. Probabilistic temporal multimedia data mining. ACM Transactions on Intelligent Systems and Technology (2011)

    Google Scholar 

  8. Biolchini, J., et al.: Systematic Review in Software Engineering. COPPE/UFRJ Technical Report RT-ES 679/05, Rio de Janeiro (May 2005)

    Google Scholar 

  9. Calders, T., Garboni, C., Goethals, B.: Efficient pattern mining of uncertain data with sampling. In: Zaki, M.J., Yu, J.X., Ravindran, B., Pudi, V. (eds.) PAKDD 2010, Part I. LNCS, vol. 6118, pp. 480–487. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  10. Chau, M., Cheng, R., Kao, B.: Uncertain Data Mining: A New Research Direction. In: Workshop on the Sciences of the Artificial, Hualien, Taiwan, December 7-8 (2005)

    Google Scholar 

  11. Chen, Y., Weng, C.: Mining association rules from imprecise ordinal data. Fuzzy Sets and Systems (2008)

    Google Scholar 

  12. Chui, C.-K., Kao, B., Hung, E.: Mining Frequent Itemsets from Uncertain Data. In: Zhou, Z.-H., Li, H., Yang, Q. (eds.) PAKDD 2007. LNCS (LNAI), vol. 4426, pp. 47–58. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  13. Chui, C.-K., Kao, B.: A decremental approach for mining frequent itemsets from uncertain data. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 64–75. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  14. Gao, F., Wu, C.: Mining frequent itemset from uncertain data. In: ICECE 2011 (2011)

    Google Scholar 

  15. Han, J., Pei, J., Yin, Y.: Mining frequent patterns without candidate generation. SIGMOD (2000)

    Google Scholar 

  16. Han, J., Kamber, M., Pei, J.: Data Mining Concepts and Tecniques. Morgan Kaufmann (2011)

    Google Scholar 

  17. Hanneman, R.A., Riddle, M.: Introduction to social network methods. Univ Calif. Riverside (2005), http://faculty.ucr.edu/~hanneman/

  18. Herawan, T., Deris, M.: A soft set approach for association rules mining. Knowledge-Based Systems (2011)

    Google Scholar 

  19. Kadri, O., Ezeife, C.I.: Mining uncertain web log sequences with access history probabilities. In: ACM SAC (2011)

    Google Scholar 

  20. Khan, A., Yan, X., Wu, K.L.: Towards proximity pattern mining in large graphs. In: ACM SIGMOD (2010)

    Google Scholar 

  21. Kitchenham, B.: Guidelines for performing Systematic Literature Reviews in Software Engineering. Keele Univ. EBSE Tech. Rep. EBSE-2007-01, UK (2007)

    Google Scholar 

  22. Lee, Y., Hong, T., Wang, T.: Multi-level fuzzy mining with multiple minimum supports. Expert Systems with Applications (2008)

    Google Scholar 

  23. Leung, C.K.-S., Mateo, M.A.F., Brajczuk, D.A.: A tree-based approach for frequent pattern mining from uncertain data. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 653–661. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  24. Leung, C., Brajcsuk, D.A.: Efficient algorithms for mining constrained frequent patterns from uncertain data. In: 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data (2009)

    Google Scholar 

  25. Leung, C., Brajcsuk, D.A.: Mining uncertain data for constrained frequent sets. In: IDEAS (2009)

    Google Scholar 

  26. Leung, C., Hao, B., Brajcsuk, D.A.: Mining uncertain data for frequent itemsets that satisfy aggregate constraints. In: ACM SAC (2010)

    Google Scholar 

  27. Leung, C., Brajcsuk, D.A.: uCFS2: an enhanced system that mines uncertain data for constrained frequent sets. In: IDEAS (2010)

    Google Scholar 

  28. Leung, C., Jiang, F., Hayduk, Y.: A landmark-model based system for mining frequent patterns from uncertain data streams. In: 15th IDEAS (2011)

    Google Scholar 

  29. Leung, C., Sun, L.: Equivalence class transformation based mining of frequent itemsets from uncertain data. In: ACM SAC (2011)

    Google Scholar 

  30. Leung, C., Jiang, F.: Frequent itemset mining of uncertain data streams using the damped window model. In: ACM SAC (2011)

    Google Scholar 

  31. Lin, C., Hong, T.: A new mining approach for uncertain databases using CUFP trees. Expert Systems with Applications (2012)

    Google Scholar 

  32. Liu, Y.: Mining frequent patterns from univariate uncertain data. Data and Knowledge Engineering (2012)

    Google Scholar 

  33. Muzammal, M., Raman, R.: On probabilistic models for uncertain sequential pattern mining. In: Cao, L., Feng, Y., Zhong, J. (eds.) ADMA 2010, Part I. LNCS, vol. 6440, pp. 60–72. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  34. Muzammal, M., Raman, R.: Mining sequential patterns from probabilistic databases. In: Huang, J.Z., Cao, L., Srivastava, J. (eds.) PAKDD 2011, Part II. LNCS, vol. 6635, pp. 210–221. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  35. Muzammal, M.: Mining sequential patterns from probabilistic databases by pattern-growth. In: 28th British National Conference on Databases (2011)

    Google Scholar 

  36. Özyer, T., Alhajj, R., Barker, K.: Intrusion detection by integrating boosting genetic fuzzy classifier and data mining criteria for rule pre-screening. Network and Computer Applications (2007)

    Google Scholar 

  37. Papapetrou, O., Ioannou, E., Skoutas, D.: Efficient discovery of frequent subgraph patterns in uncertain graph databases. In: 14th EDBT (2011)

    Google Scholar 

  38. Pei, J., et al.: H-mine: hyper-structure mining of frequent patterns in large databases. In: ICDM (2001)

    Google Scholar 

  39. Qin, X., Zhang, Y., Li, X., Wang, Y.: Associative classifier for uncertain data. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) WAIM 2010. LNCS, vol. 6184, pp. 692–703. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  40. Sun, L., et al.: Mining uncertain data with probabilistic guarantees. In: ACM SIGKDD (2010)

    Google Scholar 

  41. Sun, X., Lim, L., Wang, S.: An approximation algorithm of mining frequent itemsets from uncertain dataset. Intl. Journal of Advancements in Computing Technology (2012)

    Google Scholar 

  42. Tang, P., Peterson, E.A.: Mining probabilistic frequent closed itemsets in uncertain databases. In: 49th Annual Southeast Regional Conference (2011)

    Google Scholar 

  43. The R Project for Statistical Computing, http://www.r-project.org/ (accessed on October 8, 2012)

  44. Wang, L., et al.: Accelerating probabilistic frequent itemset mining: a model-based approach. In: 19th ACM CIKM (2010)

    Google Scholar 

  45. Yin, P., Li, S.: Content-based image retrieval using association rule mining with soft relevance feedback. Visual Communication and Image Representation (2006)

    Google Scholar 

  46. Zaki, M., et al.: New algorithms for fast discovery of association rules. In: ACM SIGKDD (1997)

    Google Scholar 

  47. Zou, Z., et al.: Frequent subgraph pattern mining on uncertain graph data. In: CIKM (2009)

    Google Scholar 

  48. Zou, Z., Gao, H., Li, J.: Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics. In: ACM SIGKDD (2010)

    Google Scholar 

  49. Zou, Z., et al.: Mining frequent subgraph patterns from uncertain graph data. IEEE Transactions on Knowledge and Data Engineering (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computing Science Graduate Program – Faculty of Informatics, Pontifical Catholic University of RS - PUCRS, Porto Alegre, RS, Brazil

    Juliano Varella de Carvalho & Duncan Dubugras Ruiz

Authors
  1. Juliano Varella de Carvalho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Duncan Dubugras Ruiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

de Carvalho, J.V., Ruiz, D.D. (2013). Discovering Frequent Itemsets on Uncertain Data: A Systematic Review. In: Perner, P. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2013. Lecture Notes in Computer Science(), vol 7988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39712-7_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39712-7_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39711-0

  • Online ISBN: 978-3-642-39712-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation