Abstract
Association rule mining plays a crucial role in many of the business organizations like retail, telecommunications, manufacturing, insurance, banking, etc., to identify association among different objects in the dataset. In the process of rule mining, identify frequent patterns, which can help to improve the business decisions. FP-growth and CP-tree are the well-known algorithms to find the frequent patterns. This work performs comparative analysis of FP-growth and CP (compact pattern)-tree based on time and space complexity parameters. The comparative analysis also focuses on scalability parameter with various benchmark dataset sizes. Outcomes of this work help others to choose the algorithm to implement in their application.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Patro, S.N., Mishra, S., Khuntia, P., et. al.: Construction of FP-tree using Huffman Coding. Int. J. Comput. Sci. (IJCSI) 9(3), 2 (May 2012)
Tanbeer, S.K., Ahmed, C.F., Jeong, B.-S., Lee, Y.-K.: Efficient single-pass frequent pattern mining using a prefix-tree. Inf. Sci. (Elsevier) 179, 559–583 (2008). https://doi.org/10.1016/j.ins.2008.10.027
Shrivastava, N., Khanna, R.: FP-Growth tree based algorithms analysis: CP-Tree and K Map. Bin. J. Data Min. Netw. 5, 26–29 (2015). ISSN: 2229-7170
Pandya, M., Trikha, P.: A new tree structure to extract frequent pattern. Int. J. Emerg. Technol. Adv. Eng 3(3) (March 2013). ISSN: 2250-2459
Ghatage, R. A.: Frequent pattern mining over data stream using compact sliding window tree & sliding window model. Int. Res. J. Eng. Technol. (IRJET) 02(04) (July 2015). p-ISSN: 2395-0072, e-ISSN: 2395-0056
Pandya, M., Trikha, P.: An efficient prefix tree structure to extract frequent pattern. Int. J. Adv. Eng. Technol. 6(3), 1220–1227 (July 2013)
Zhang, S., Zhang, J., Zhang, C.: EDUA: an efficient algorithm for dynamic database mining. Inf. Sci. (Elsevier) 177, 2756–2767 (2007)
Srimania, P.K., Patilb, M.M.: Frequent item set mining using INC_MINE. In: Massive Online Analysis Frame work, Science Direct, Procedia Computer Science, vol. 45, pp. 133–142. (Elsevier) (2015)
Meenakshi, A.: Survey of frequent pattern mining algorithms in horizontal and vertical data layouts. Int. J. Adv. Comput. Sci. Technol. ISSN 4(4), 2320–2602 (April 2015)
Nasreen, S., Azam, M.A., Shehzad, K., et.al.: Frequent pattern mining algorithms for finding associated frequent patterns for data streams. In: A Survey, International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN) Science Direct, Pro: Computer Science, vol. 37, pp. 109–116 (2014)
Koh, Y.S., Dobbie, G.: SPO-Tree: Efficient Single Pass Ordered Incremental Pattern Mining. Springer, Berlin, vol. 6862, pp. 265–276 (2011). https://doi.org/10.1007/978-3-642-23544-3-20
Lodhi, N.S., Dangra, J., Rawat, M.K.: A compact table based time efficient technique for mining frequent items from a transactional data base. Int. J. Adv. Res. Comput. Sci. Softw. Eng. 5(1) (January 2015). ISSN: 2277 128X
Fole, M.D., Choudhary, C.: Finding an efficient approach for generating frequent patterns in large database. Int. J. Adv. Res. Comput. Eng. Technol. (IJARCET) 4(2) (Februray 2015)
Narvekar, M., Syed, S.F.: An optimized algorithm for association rule mining using FP Tree. Procedia Comput. Sci. (Elsevier) 45, 101–110 (2015)
Shashikumar, G., Totad, R.B., Geeta, P.V.G.D., Reddy, P.: Batch incremental processing for FP-tree construction using FP-Growth algorithm. In: Knowledge and Information Systems. Springer (2012). https://doi.org/10.1007/s10115-012-0514-9
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Annapoorna, V., Rama Krishna Murty, M., Hari Priyanka, J.S.V.S., Chittineni, S. (2018). Comparative Analysis of Frequent Pattern Mining for Large Data Using FP-Tree and CP-Tree Methods. In: Satapathy, S., Tavares, J., Bhateja, V., Mohanty, J. (eds) Information and Decision Sciences. Advances in Intelligent Systems and Computing, vol 701. Springer, Singapore. https://doi.org/10.1007/978-981-10-7563-6_7
Download citation
DOI: https://doi.org/10.1007/978-981-10-7563-6_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7562-9
Online ISBN: 978-981-10-7563-6
eBook Packages: EngineeringEngineering (R0)