A Survey on Relational Database Based Multi Relational Classification Algorithms

Authors

  • Komal Shah Research Scholar, Gujarat Technological University, Ahmedabad, Gujarat, India Author
  • Dr. Kajal S. Patel Associate Professor, Vishwakarma Government Engineering College affiliated to Gujarat Technological University, Ahmedabad, Gujarat, India Author

DOI:

https://doi.org/10.32628/CSEIT2390656

Keywords:

Data Mining, Classification, Relational Data, Multirelational Classification

Abstract

Classification on real world database is an important task in data mining. Many classification algorithms can build model only for data in single flat file as input, whereas most of real-world data bases are stored in multiple tables and managed by relational database systems. As conversion of relational data from multiple tables into a single flat file usually causes many problems, development of multi relational classification algorithms becomes popular area of research interests. Relational database based multi relational classification algorithms aim to build a model that can predict class label of unknown tuple with the help of background table knowledge.  This method keeps database in it normalized form without distorting structure of database. This paper presents survey of existing multi relational classification algorithms based on relational database.

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References

Jiawei Han, Micheline Kamber, Data Mining: Concepts and Techniques 2nd, China Machine Press, Beijing, 2006.

Kramer, S., N. Lavrac and P. Flach. Propositionalization approaches to relational data mining. In S. Dzeroski and N. Lavrac, eds. Relational Data Mining. pp 262-291, Springer- Verlag, 2001. DOI: https://doi.org/10.1007/978-3-662-04599-2_11

H. Blockeel, "Statical relational learning," handbook on Neural network Information Processing, 2013. DOI: https://doi.org/10.1007/978-3-642-36657-4_8

Jing-Feng Guo, An Efficient Relational Decision Tree Classification Algorithm, Third International Conference on Natural Computation (ICNC 2007).

X., Han, J., Yang, J., & Philip, S. Y. Yin, "Crossmine: Efficient classification across multiple database relations," In Constraint-Based mining and inductive databases. Springer, Berlin, Heidelberg., pp. 172-195, 2006. DOI: https://doi.org/10.1007/11615576_9

Héctor Ariel Leiva, "MRDTL: A multi-relational decision tree learning algorithm," 2002.

Knobbe, J., Blockeel, H., Siebes, A., and Van der Wallen, D. M. G. Multi-relational Data Mining. In Proceedings of Benelearn ’99, 1999. DOI: https://doi.org/10.1007/3-540-45372-5_1

A., Leiva, H., & Honavar, V. Atramentov, "A multi-relational decision tree learning algorithm–implementation and experiments.," 38-56, 2003. DOI: https://doi.org/10.1007/978-3-540-39917-9_5

X., Han, J., Yang, J., & Philip, S. Y. Yin, "Efficient classification across multiple database relations: A crossmine approach," IEEE Transactions on Knowledge & Data Engineering, (6), pp. 770-783.

H., Yin, X., & Han, J. Liu, "An efficient multi-relational Naïve Bayesian classifier based on semantic relationship graph," In Proceedings of the 4th international workshop on Multi-relational mining. ACM., pp. 39-48, 2005.

H., Liu, H., Han, J., Yin, X., & He, J. Chen, "Exploring optimization of semantic relationship graph for multi-relational Bayesian classification," ecision Support Systems, 48(1), pp. 112-121, 2009. DOI: https://doi.org/10.1016/j.dss.2009.07.004

G., Murty, M. N., & Sitaram, D. Manjunath, "A heterogeneous naive-bayesian classifier for relational databases.," KDD, Paris., 2009.

O., Bina, B., Crawford, B., Bingham, D., & Xiong, Y. Schulte, "A hierarchy of independence assumptions for multi-relational Bayes net classifiers," IEEE Symposium on Computational Intelligence and Data Mining (CIDM), pp. 150-159, 2013.

R., Moser, F., & Ester, M. Frank, "A method for multi-relational classification using single and multi-feature aggregation functions.," In European Conference on Principles of Data Mining and Knowledge Discovery. Springer, Berlin, Heidelberg., pp. 430-437, 2007.

J., Liu, H., Hu, B., Du, X., & Wang, P. He, "Selecting Effective Features And Relations For Efficient Multi‐Relational Classification," Computational Intelligence, 26(3), pp. 258-281, 2010 DOI: https://doi.org/10.1111/j.1467-8640.2010.00359.x

H., & Viktor, H. L. Guo, "Mining relational databases with multi-view learning," In Proceedings of the 4th international workshop on Multi-relational mining, ACM, pp. 15-24, 2005.

H., & Viktor, H. L. (2006, July). Guo, "Multi-view ANNs for multi-relational classification. In Neural Networks," IJCNN'06. International Joint Conference on (pp. 5259-5266). IEEE., 2006.

Viktor Herna L. Guo Hongyu, "Mining relational data through correlation-based multiple view validation," In Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining ACM., pp. 567-573, 2006.

S. Modi, "Relational classification using multiple view approach with voting," International Journal of Computer Applications, 70(16)., 2013. DOI: https://doi.org/10.5120/12153-8126

A., & Kosta, Y. P. Thakkar, "Efficient Heterogeneous Multi-relational Classification Using Multi-criteria Ranking Approach Based on Characteristics of Multiple Relations.," JCP, 10(6), pp. 418-426, 2015. DOI: https://doi.org/10.17706/jcp.10.6.418-426

Kosta, Y. P. Thakkar Amit, "Improving efficiency of heterogeneous multi relational classification by choosing efficient classifiers using ratio of success rate and time," Intelligent Automation & Soft Computing, 23(1), pp. 75-86, 2017. DOI: https://doi.org/10.1080/10798587.2015.1136106

Srinivasan, A., Muggleton, S.H., Sternberg, M.J., & King, R.D. (1996). Theories for mutagenicity: A study in first-order and feature-based induction. Artificial Intelligence, 85, 277–299. DOI: https://doi.org/10.1016/0004-3702(95)00122-0

Berka, P., (2000) Guide to the financial data set. In A. Siebes & P. Berka (Eds.), PKDD2000 Discovery Challenge.

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Published

15-03-2024

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Section

Research Articles

How to Cite

[1]
K. Shah and K. S. Patel, “A Survey on Relational Database Based Multi Relational Classification Algorithms”, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, vol. 10, no. 2, pp. 140–147, Mar. 2024, doi: 10.32628/CSEIT2390656.

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