Understanding Complex Datasets

Presenting the underlying matrix theory and explaining its effectiveness as a tool, this work demonstrates how to build models of complex data using real-world scientific and engineering systems, and focuses on a range of applications such as information retrieval, topic detection, and social network analysis.

Inhalt

Data Mining. Matrix Decompositions. Singular Value Decomposition (SVD). Graph Analysis. SemiDiscrete Decomposition (SDD). Using SVD and SDD Together. Independent Component Analysis (ICA). Non-Negative Matrix Factorization (NNMF). Tensors. Conclusion. Appendix. Bibliography. Index.