Understanding Complex Datasets: Data Mining with Matrix Decompositions

@inproceedings{Liu2007UnderstandingCD,
  title={Understanding Complex Datasets: Data Mining with Matrix Decompositions},
  author={Huan Liu and Hiroshi Motoda and Sugato Basu and Ian Davidson and Kiri L. Wagstaff and Mehran Sahami and PuBLISHeD TITLeS and SeRIeS eDITOR and Vipin Kumar and Ashok N. Srivastava},
  year={2007}
}
  • Huan Liu, Hiroshi Motoda, +7 authors Ashok N. Srivastava
  • Published 2007
DATA MINING What Is Data Like? Data Mining Techniques Why Use Matrix Decompositions? MATRIX DECOMPOSITIONS Definition Interpreting Decompositions Applying Decompositions Algorithm Issues SINGULAR VALUE DECOMPOSITION (SVD) Definition Interpreting an SVD Applying SVD Algorithm Issues Applications of SVD Extensions GRAPH ANALYSIS Graphs versus Datasets Adjacency Matrix Eigenvalues and Eigenvectors Connections to SVD Google's PageRank Overview of the Embedding Process Datasets versus Graphs… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 84 CITATIONS

Identifying candidates for design-by-analogy

VIEW 12 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Touch and Move: Incoming Call User Authentication

VIEW 7 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2007
2019

CITATION STATISTICS

  • 21 Highly Influenced Citations

References

Publications referenced by this paper.
SHOWING 1-10 OF 49 REFERENCES

Document clustering with prior knowledge

  • SIGIR
  • 2006
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

Feature Weighting in k-Means Clustering

VIEW 10 EXCERPTS
HIGHLY INFLUENTIAL

Y-means: a clustering method for intrusion detection

  • CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436)
  • 2003
VIEW 8 EXCERPTS
HIGHLY INFLUENTIAL

A framework for finding projected clusters in high dimensional spaces

C C.Aggarwal, C. Procopiuc, J L.Wolf, P S.Yu, J.-S. Park
  • Proceedings of the ACM SIGMOD Conference on Management of Data,
  • 1999
VIEW 7 EXCERPTS
HIGHLY INFLUENTIAL