Mining association rules using non-negative matrix factorization and formal concept analysis

Communications in Computer and Information Science

Volumn 157 CCIS, Issue , 2011, Pages 31-39

  Aswani Kumar, Ch ^a  

^a VIT UNIVERSITY   (India)

Author keywords

Association rules mining; Concept lattice; Dimensionality reduction; Formal concept analysis; Non Negative matrix factorization; Singular value decomposition

Indexed keywords

ASSOCIATION RULES MINING; CONCEPT LATTICES; DIMENSIONALITY REDUCTION; FORMAL CONCEPT ANALYSIS; NONNEGATIVE MATRIX FACTORIZATION; SINGULAR VALUES;

ASSOCIATION RULES; BLIND SOURCE SEPARATION; DATA MINING; DATA PROCESSING; HEALTH CARE; INTELLIGENT COMPUTING; SINGULAR VALUE DECOMPOSITION;

FACTORIZATION;

EID: 83355163305     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-22786-8_4     Document Type: Conference Paper

References (17)

1. Priss, U.: Formal Concept Analysis in Information Science. Annual Review of Information Science and Technology 40(1), 521-543 (2007)
2. Snasel, V., Polovincak, M., Dahwa, H.M., Horak, Z.: On Concept Lattices and Implication Bases from Reduced Contexts. In: Proc. of ICCS Supplement, pp. 83-90 (2008)
3. Aswani Kumar, C.: Analysis of Unsupervised Dimensionality Reduction Techniques. Computer Science and Information Systems 6(2), 217-227 (2009)
4. Wu, W.Z., Leung, Y., Mi, J.S.: Granular Computing and Knowledge Reduction in Formal Contexts. IEEE Transactions on Knowledge and Data Engineering 21, 1461-1474 (2009)
5. Snasel, V., Gajdos, P., Abdulla, H.M.D., Polovincak, M.: Using matrix decompositions in formal concept analysis. In: Proc. of the 10th International Conference on Information Systems Implementation and Modeling (2007)
6. Snasel, V., Abdulla, H.M.D., Polovincak, M.: Behavior of the Concept Lattice Reduction to Visualizing Data after using Matrix decomposition. In: Proc. of 4th International Conference on Innovations in Information Technology, pp. 392-396 (2008)
7. Aswani Kumar, C., Srinivas, S.: Concept Lattice Reduction using Fuzzy k means Clustering. Expert Systems with Applications 37(3), 2696-2704 (2010)
8. Aswani Kumar, C., Srinivas, S.: Mining Associations in Health Care Data using Formal Concept Analysis and Singular Value Decomposition. Journal of Biological Systems 18(4), 787-807 (2010)
9. Aswani Kumar, C., Srinivas, S.: Latent Semantic Indexing using Eigenvalue Analysis for Efficient Information Retrieval. International Journal of Applied Mathematics and Computer Science 16(4), 551-558 (2006)
10. Stumme, G.: Formal Concept Analysis, Handbook of Ontologies, pp. 177-199. Springer, Heidelberg (2009)
11. Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical foundations. Springer, Heidelberg (1999)
12. Krotzsch, M., Ganter, B.: A Brief Introduction to Formal Concept Analysis. In: Hitzler, P., Scharfe, H. (eds.) Conceptual Structures in Practice, pp. 3-16. CRC Press, Boca Raton (2009)
13. Lee, D.D., Seung, H.S.: Algorithms for Non-Negative Matrix Factorization. Advances in Neural Information Processing 13, 556-562 (2001)
14. Divya, R., Aswani Kumar, C., Saijanani, S., Priyadarshini, M.: Deceiving Communication Links on an Organization Email Corpus. Malaysian Journal of Computer Science 24(1), 17-33 (2011)
15. Horner, V.: Developing a Consumer Health Informatics Decision Support System using Formal Concept Analysis, Masters Thesis, University of Pretoria (2007)
16. Dias, S.M., Vicira, N.J.: Reducing the Size of Concept Lattices: The JBOS approach. In: Kryszkiewicz, M., Obiedkov, S. (eds.) Proc. CLA 2010, pp. 60-69 (2010)
17. Aswani Kumar, C.: Knowledge Discovery in Data using Formal Concept Analysis and Random Projections. International Journal of Applied Mathematics and Computer Science (accepted 2011)