Abstract
Association rules are one of the most used data mining techniques. The first proposals have considered relations over time in different ways, resulting in the so-called temporal association rules (TAR). Although there are some proposals to extract association rules in OLAP systems, to the best of our knowledge, there is no method proposed to extract temporal association rules over multidimensional models in these kinds of systems. In this paper, we study the adaptation of TAR to multidimensional structures, identifying the dimension that establishes the number of transactions and how to find time relative correlations between the other dimensions. A new method called COGtARE is presented as an extension of a previous approach proposed to reduce the complexity of the resulting set of association rules. The method is tested in application to financial data of companies.
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References
Agrawal R, Sritkant R (1994) Fast algorithms for mining association rules in large databases. In: Proceedings of 20th international conference on very large data bases, pp 478–499
Tung AK, Lu H, Han J, Feng L (1999) Breaking the barrier of transactions. In: Proceedings of the fifth ACM SIGKDD international conference on knowledge discovery and data mining—KDD ‘99. ACM Press
Lu H, Han J, Feng L (1998) In: ACM SIGMOD workshop on research issues on data mining and knowledge discovery. Seattle, WA, USA, ACM, New York, USA
Srikant R, Naughton JF (1996) Fast algorithms for mining association rules and sequential patterns. Ph.D. thesis. AAI9708697
Ozden B, Ramaswamy S, Silberschatz A, Cyclic association rules. In: Proceedings 14th international conference on data engineering. IEEE Computer Society
Li Y, Ning P, Wang XS, Jajodia S (2003) Discovering calendar-based temporal association rules. Data Knowl Eng 44(2):193–218
Hopner F, Klawonn F (2002) Finding informative rules in interval sequences. Intell Data Anal 6(3):237–255
Segura-Delgado A, Gacto MJ, Alcalá R, Alcalá-Fdez J (2020) Temporal association rule mining: an overview considering the time variable as an integral or implied component. WIREs Data Min Knowl Discov 10(4):e1367
Codd EF (1993) Providing OLAP (On-line Analytical Processing) to user-analysts: an IT mandate. E.F. Codd and Associates, Technical report
Zhu H (1998) On-line analytical mining of association rules. Ph.D. thesis, Simon Fraser University
Marín N, Molina C, Serrano JM, Vila A (2008) A complexity guided algorithm for association rule extraction on fuzzy datacubes. IEEE Trans Fuzzy Syst 16:693–714
Marín N, Molina C, Serrano JM, Vila A (2008) A complexity guided algorithm for association rule extraction on fuzzy datacubes. IEEE Trans Fuzzy Syst 16:693–714
Shortliffe E, Buchanan B (1975) A model of inexact reasoning in medicine. Math Biosci 23:351–379
Delgado M, Marin N, Sanchez D, Vila MA (2003) Fuzzy association rules: general model and applications. IEEE Trans Fuzzy Syst 11(2):214–225
Acknowledgements
This research is partially supported by FEDER/Junta de Andalucía-Consejería de Transformacion Ecnonómica, Conocimiento y Universidades/ADIM: Accesibilidad de Datos para Investigación Médica (B-TIC-744-UGR20).
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Molina, C., Prados-Suárez, B. (2024). Extracting Temporal Association Rules Over Datacubes. In: Yang, XS., Sherratt, R.S., Dey, N., Joshi, A. (eds) Proceedings of Eighth International Congress on Information and Communication Technology. ICICT 2023. Lecture Notes in Networks and Systems, vol 695. Springer, Singapore. https://doi.org/10.1007/978-981-99-3043-2_48
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DOI: https://doi.org/10.1007/978-981-99-3043-2_48
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