Construction Search Engine Based on Formal Concept Analysis and Association Rule Mining

Article Preview

Abstract:

In the form of background in the form of concept partial relation to the corresponding concept lattice, concept lattice is the core data structure of formal concept analysis. Association rule mining process includes two phases: first find all the frequent itemsets in data collection, Second it is by these frequent itemsets to generate association rules. This paper analyzes the association rule mining algorithms, such as Apriori and FP-Growth. The paper presents the construction search engine based on formal concept analysis and association rule mining. Experimental results show that the proposed algorithm has high efficiency.

You have full access to the following eBook

Info:

Periodical:

Pages:

625-630

Citation:

Online since:

September 2012

Authors:

Export:

Share:

Citation:

[1] Ganter B, Wille R. Formal Concept Analysis: Mathematical Foundations [M]. Springer Verlag , Berlin, (1999).

Google Scholar

[2] C.H. Cai, W.C. Fu Ada, C.H. Cheng, W.W. Kwong. Mining association rules with weighted items.In Proc. of the Int'l Database Engineering and Applications Symposium. 1998. 68~77.

Google Scholar

[3] Ho T B. Incremental conceptual clustering in the framework of Galois lattice, in KDD: Techniques and Applications, H. Lu, H. Motoda and H. Luu (Eds. ), World Scientific, 1997. 49-64.

Google Scholar

[4] Wang L-D., Liu X-D. Concept analysis via rough set and AFS algebra Information Sciences 2008, 178(21), 4125-4137.

DOI: 10.1016/j.ins.2008.07.004

Google Scholar

[5] Anderson, B. and Moore, A. Adtrees for fast counting and for fast learning of association rules. KDD-98. USA. (1998).

Google Scholar

[6] Faïd M, Missaoui R, Godin R. Knowledge discovery in complex objects. Computational Intelligence, 1999, 15(1): 28-49.

DOI: 10.1111/0824-7935.00080

Google Scholar