Fatima Zahra El Mazouri
ABSTRACT
Pattern discovery is one of the most important tasks in data mining, many works are developed in this context where we can notice the problem of 'pattern explosion' which make taking a decision about useful pattern more difficult. the goal of our study is to make an improvement in the process of extracting useful patterns from data, called also 'pattern mining'. The aim of this article is to propose an approach to select useful patterns from a set of patterns by using multicriteria approach. To do this, we will use the famous multicriteria analysis method called ELECTRE, particularly ELECTRE I, in order to have a selection of the most relevant patterns according to proposed criteria.
- Agrawal, R., Imielinski, T and Swami. N. 1993. Mining association rules between sets of items. In large databases. In ACM SIGMOD International Conference on Management of Data, 207--216. Baltimore: ACM Press. Google Scholar
Digital Library
- M. J. Zaki and K. Sequeira, "Data mining in computational biology" in Handbook of Computational Molecular Biology. Chapman & Hall/CRC Press, 2006, ch. 38, p. 1 -26.Google Scholar
- J. Auer and J. Bajorath, Emerging chemical patterns: A new methodology for molecular classification and compound selection, J. Chem. Inf. Mod, vol. 46, no. 6, p. 2502--2514, 2006.Google ScholarCross Ref
- H. Mannila and H. Toivonen, "Levelwise search and borders of theories in knowledge discovery," DMKD, vol. 1, no. 3, p. 241 -258, 1997. Google ScholarDigital Library
- R. Agrawal, T. Imielinski, A. Swami, Mining association rules between sets of items in large databases, ACM SIGMOD Rec. 22 (2) (1993) 207--216. Google ScholarDigital Library
- Moonjung Cho, Jian Pei, Haixun Wang, Wei Wang, Preference-based Frequent Pattern Mining.International Journal of Data Warehous and Mining (IJDWM), 1(4) 2005 pages:22.Google Scholar
- A. Soulet and B. Crémilleux, "Mining constraint-based patterns using automatic relaxation," Intell Data Anal, vol. 13, no. 1, p. 109--133, 2009. Google ScholarDigital Library
- B. Roy, D. Bouyssou, Aide multicritère méthodes et cas, Economica, Paris, 1993.Google Scholar
- K. Pushpalatha, V.S. Ananthanarayana, A tree based representation for effective pattern discovery from multimedia documents, Pattern Recognition Letters. 000 (2016) 1--11.Google Scholar
- L. Maystre, J. Pictet, J. Simos, Méthode multicritère ELECTRE, Presses Polytechniques et Universitaires Romandes (PPUR), 1994, 340 pages.Google Scholar
- J. Neesha, A.R. Nur'Aini, H. Wahidah, Data Mining in Healthcare - A Review, Procedia Computer Science. 72 (2015) 306--313.Google ScholarCross Ref
- Hedieh Sajedi, Steganalysis based on steganography pattern Discovery, journal of information security and applications. 30 (2 0 1 6) 3--14. Google ScholarDigital Library
- Asif R., Merceron A., Ali S.A. & Haider N.G., Analyzing undergraduate students' performance using educational data mining, Computers & Education (2017),Google Scholar
- Shashi Shekhar, Yan Li, Reem Y. Ali, Emre Eftelioglu, Zhe Jiang, Spatial and Spatiotemporal Data Mining, Comprehensive Geographic Information Systems, 2018, Pages 264--286.Google Scholar
- J. Neesha, A.R. Nur'Aini, H. Wahidah, Data Mining in Healthcare - A Review, Procedia Computer Science. 72 (2015) 306--313.Google ScholarCross Ref
- Ila Dutta, Shantanu Dutta, Bijan Raahemi, Detecting Financial Restatements Using Data Mining Techniques, Expert Systems With Applications (2017), Google ScholarDigital Library
- David E. Jones, Hamidreza Ghandehari, Julio C. Facelli, A review of the applications of data mining and machine learning for the prediction of biomedical properties of nanoparticles, Computer Methods and Programs in Biomedicine (2016), Google ScholarDigital Library
- Eva Armengol, Dion«õs Boixader, Francisco Grimaldo, Special Issue on Pattern Recognition Techniques in Data Mining, Pattern Recognition Letters (2017),Google Scholar
- Ashis Kumar Chanda, Chowdhury Farhan Ahmed, Md. Samiullah, Carson K. Leung, A new framework for mining weighted periodic patterns in time series databases, Expert Systems with Applications (2017),Google Scholar
- Giovanni Montana, Stefan Van Aelst, Ruben H. Zamar, Special Issue on Advances in Data Mining and Robust Statistics, Computational Statistics and Data Analysis 93 (2016) 388--389. Google ScholarDigital Library
- Shahab Dean Mohaghegh, Reservoir simulation and modeling based on artificial intelligence and data mining (AI&DM), Journal of Natural Gas Science and Engineering. 3 (2011) 697--705.Google ScholarCross Ref
- M. Mousavi, H. Gitinavard, S.M. Mousavi, A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information Renewable and Sustainable Energy Reviews, Volume 68, Part 1, February 2017, Pages 774--78.Google Scholar
- Getnet D. Betrie, Rehan Sadiq, Kevin A. Morin, Solomon Tesfamariam, Selection of remedial alternatives for mine sites: A multicriteria decision analysis approach, Journal of Environmental Management, Volume 119, 15 April 2013, Pages 36--46.Google ScholarCross Ref
- Roy, Bernard (1968). "Classement et choix en présence de points de vue multiples (la méthode ELECTRE)". La Revue d'Informatique et de Recherche Opérationelle (RIRO) (8): 57--75.Google Scholar
- A.-M. Addi, A. Tarik; G. Fatima, "Comparative survey of association rule mining algorithms based on multiple criteria decision analysis approach". In Control, Engineering & Information Technology (CEIT), 2015 3rd International Conference on, vol., no., pp. 1--6, 25-27 May 2015.Google Scholar
- S. Jabbour, S. Kaci, L. Sais, Y. Salhi, Penalty based Preferences in Itemset Mining, Association for the Advancement of Artificial Intelligence (www.aaai.org).Google Scholar
- Arnaud Soulet, Chedy Raissi, Marc Plantevit, Bruno Crémilleux, Mining Dominant Patterns in the Sky, 11th IEEE International Conference on Data Mining 2011. Google ScholarDigital Library
- A. Histace, M. Ménard, C. Cavaro-Ménard, Selective diffusion for oriented pattern extraction: Application to tagged cardiac MRI enhancement, Journal of Pattern Recognition Letters 30 (2009) 1356--1365. Google ScholarDigital Library
- V. Pouget, S. Jonathas, R. Job, J.R. Vaillé, F.Wrobel, F. Saigné, Structural pattern extraction fromasynchronous two-photon laser fault injection using spectral analysis, Microelectronics Reliability, In press, No of pages 5.Google Scholar
- Bernardete Ribeiro, Ning Chen, Alexander Kovacec, Shaping Graph Pattern Mining for Financial Risk, Neurocomputing (2017),Google Scholar
- Peter Liang, Yingzhen Yang, Yang Cai, Pattern mining from saccadic motion data, Procedia Computer Science 1 (2010) 2529--2538.Google ScholarCross Ref
- Shamila Nasreen, Muhammad Awais Azam, Khurram Shehzad, Usman Naeem, Mustansar Ali Ghazanfar, Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey, Procedia Computer Science 37 (2014) 109 -116.Google ScholarCross Ref
- Y. Ke, J. Cheng, and J. X. Yu, "Top-k correlative graph Mining". In SIAM DM, 2009, p. 1038--1049.Google Scholar
- J. Wang, J. Han, Y. Lu, and P. Tzvetkov, "TFP: An efficient algorithm for mining top-k frequent closed itemsets, " TKDE, vol. 17, p. 652--664, 2005. Google ScholarDigital Library
Recommendations
An efficient approach to mine periodic-frequent patterns in transactional databases
PAKDD'11: Proceedings of the 15th international conference on New Frontiers in Applied Data MiningRecently, temporal occurrences of the frequent patterns in a transactional database has been exploited as an interestingness criterion to discover a class of user-interest-based frequent patterns, called periodic-frequent patterns. Informally, a ...
Discovering Periodic-Frequent Patterns in Transactional Databases
PAKDD '09: Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data MiningSince mining frequent patterns from transactional databases involves an exponential mining space and generates a huge number of patterns, efficient discovery of user-interest-based frequent pattern set becomes the first priority for a mining algorithm. ...
The Studies of Mining Frequent Patterns Based on Frequent Pattern Tree
PAKDD '09: Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data MiningMining frequent patterns is to discover the groups of items appearing always together excess of a user specified threshold. Many approaches have been proposed for mining frequent pattern. However, either the search space or memory space is huge, such ...
Comments