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Research on Knowledge Transfer in Software Engineering by Concept Lattice Isomorphic

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 152))

Abstract

Concept lattice has many applications, e.g., software engineering, knowledge discovery. And isomorphic judgment of concept lattice is important in various fields, for instance, ontology similarity measure. In this paper, we apply the isomorphic judgment algorithm of concept lattice in software engineering to transfer knowledge in different domains after analyzed the foundation of transfer learning. Followed, an example of transfer knowledge in software engineering was introduced, and it shows the efficiency of our method.

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References

  1. Pan, S.J., Yang, Q.: A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering 22(10), 1345–1359 (2010)

    Article  Google Scholar 

  2. Hesse, W., Tilley, T.: Formal Concept Analysis Used for Software Analysis and Modelling. In: Ganter, B., Stumme, G., Wille, R. (eds.) Formal Concept Analysis. LNCS (LNAI), vol. 3626, pp. 288–303. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Xu, J.-q., Peng, X., Zhao, W.-y.: An Evolution Analysis Method Based on Fuzzy Concept Lattice and Source Code Analysis. Chinese Journal Of Computers 32(9), 1832–1844 (2009)

    Google Scholar 

  4. Li, L.-f., Zhang, D.-x.: The Application of Concept Lattice Theory in the Reduction of the Proposition Set in Two-Valued Propositional Logic. Acta Electronica Sinica 35(8), 1538–1542 (2007)

    Google Scholar 

  5. Valtchev, P., Missaoui, R., Godin, R.: Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges. In: Eklund, P. (ed.) ICFCA 2004. LNCS (LNAI), vol. 2961, pp. 352–371. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  6. du Patrick, B.-R., Bridge, D.: Collaborative Recommending using Formal Concept Analysis. Knowledge-Based Systems 19(5), 309–315 (2006)

    Article  Google Scholar 

  7. Tilley, T., Cole, R., Becker, P., Eklund, P.: A Survey of Formal Concept Analysis Support for software engineering activities. In: Proceedings of the First International Conference on Formal Concept Analysis - ICFCA 2003. Springer, Heidelberg (2003)

    Google Scholar 

  8. Ganter, B., Wille, R.: Formal Concept Analysis. Mathematical Foundations. Springer, Heidelberg (1999)

    Book  MATH  Google Scholar 

  9. Ng, P.: A Concept Lattice Approach for Requirements Validation with UML State Machine Model. In: Fifth International Conference on Software Engineering Research, Management and Applications, pp. 393–400 (2007)

    Google Scholar 

  10. Li, F., Li, X.: Isomorphism Testing Algorithm for Graphs: Incidence Degree Sequence Method and Applications. Journal of Fudan University (Natural Science) 40(3), 318–325 (2001)

    MathSciNet  MATH  Google Scholar 

  11. Zou, X.-x., Dai, Q.: A Vertex Refinement Method for Graph Isomorphism. Journal of Software (02), 213–219 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  12. Wang, Y.K., Fan, K.C., Horng, J.T.: Genetic-Based Search for Error-Correcting Graph Isomorphism. IEEE Trans. Systems, Man, and Cybernetics 27(5), 588–597 (1997)

    Article  Google Scholar 

  13. Nan, J.-H., Qi, H.: The decision-making neural networks model for solving the graph isomorphism problem. Chinese Journal of Computers 33(2), 300–304 (2010)

    Article  MathSciNet  Google Scholar 

  14. Liu, G.W., Yin, Z.X., Xu, J.: Algorithm of graph isomorphism with three dimensional DNA graph structures. Progress in Natural Science 15(2), 181–184 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Zhao, Y., Halang, W.A.: Rough concept lattice based ontology similarity measure. In: Proceedings of the First International Conference on Scalable Information Systems, Hong Kong (2006)

    Google Scholar 

  16. Han, D.-J., Li, L., Shen, X.-J.: Research on the Algorithm of Concept Lattice Isomorphic Judgment Based on Mapping of Equivalence Class. In: 2009 International Conference on Information Engineering and Computer Science, China, pp. 975–978 (December 2009)

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Li, S., Han, D., Jia, P., Shen, X. (2011). Research on Knowledge Transfer in Software Engineering by Concept Lattice Isomorphic. In: Shen, G., Huang, X. (eds) Advanced Research on Computer Science and Information Engineering. CSIE 2011. Communications in Computer and Information Science, vol 152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21402-8_31

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  • DOI: https://doi.org/10.1007/978-3-642-21402-8_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21401-1

  • Online ISBN: 978-3-642-21402-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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