Abstract
The concept lattice has played an important role in knowledge discovery. However due to inevitable occurrence of redundant information in the construction process of concept lattice, the low construction efficiency has been a main concern in the literature. In this work, an improved incremental construction algorithm of concept lattice over the traditional Godin algorithm, called the pruning based incremental algorithm is proposed, which uses a pruning process to detect and eliminate possible redundant information during the construction. Our pruning based construction algorithm is in nature superior to the Godin algorithm. It can achieve the same structure with the Godin algorithm but with less computational complexity. In addition, our pruning based algorithm is also experimentally validated by taking the star spectra from the LAMOST project as the formal context.
This paper is supported by the National Natural Science Foundation of P.R.China ( 60573075 ).
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References
Wille, R.: Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts. In: Rival, I. (ed.) Ordered sets, pp. 415–470. Reidel, Dordrecht (1982)
Wille, R.: Knowledge Acquisition by Methods of Formal Concept Analysis. In: Diday, E. (ed.) Data Analysis, Learning Symbolic and Numeric Knowledge, pp. 365–380. Nova science publisher, C. New York (1989)
Diaz-Agudo, B., Gonzalez-Calero, P.A.: Formal Concept Analysis As a Support Technique for CBR. In: Knowledge-based systems, vol. 14, pp. 163–171 (2001)
Godin, R., Missaoue, R.: An Incremental Concept Formation Approach for Learning From Database. Theoretical Computer Science 133, 387–419 (1994)
Godin, R., Missaoue, R., Alaui, H.: Incremental Concept Formation Algorithms Based on Galois (Concept) lattice. Computational Intelligence 1(2), 246–267 (1995)
Nourine, L., Raynaud, O.: A Fast Algorithm for Building Lattices. In: Workshop on Computational Graph Theory and Combinatories, C. Victoria, Canada, May, pp. 1–12 (1999)
Han, J., Kambr, M.: Data Mining Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco (2000)
Hu, K.-Y., Lu, Y.-C., Shi, C.-Y.: Advances in Concept Lattice and Its Application, vol. 40(9), pp. 77–81. Tsinghua Univ., Sci. & Tech. (2000)
Zhi-Peng, X., Zong-Tian, L.: A Fast Incremental Algorithm for Building Concept Lattice. Chinese Journal of Computers 25(5), 490–496 (2002)
Zhi-Hai, W., Ke-Yun, H., Xue-Gang, H., et al.: General And Incremental Algorithms of Rule Extraction Based On Concept Lattice. Chinese Journal of Computers 22(1), 66–70 (1999)
Hu, K.-Y., Lu, Y.-C., Shi, C.-Y.: An Integrated Mining Approach for Classification and Association Rule Based on Concept Lattice. Chinese Journal of Software 11(11), 1478–1484 (2000)
Dong-Mei, Q.: Studies on Automated Spectral Recognition of Celestial Objects. Ph.D Thesis. Institute of Automation, Chinese Academy of Sciences (2003 )
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© 2006 Springer-Verlag Berlin Heidelberg
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Ji-Fu, Z., Li-Hua, H., Su-Lan, Z. (2006). A Pruning Based Incremental Construction Algorithm of Concept Lattice. In: Perner, P. (eds) Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining. ICDM 2006. Lecture Notes in Computer Science(), vol 4065. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11790853_15
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DOI: https://doi.org/10.1007/11790853_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36036-0
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