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References for KDD work
Some important references for Data-driven Analysis of Nuclear Simulation Data. For a more comprehensive list, please visit the bibliography of the published work on "Knowledge Discovery for Nuclear Reactor Simulation Data".
Research Papers
- Efficient algorithms for mining outliers from large data sets
- On-line Monitoring for improving performance of Nuclear Power Plants
- LOF: Local Outlier Factor
- Outlier Detection by Active Learning
- On Estimation of a Probability Density Function and Mode
- Anomaly Detection: A Survey On Estimation of a Probability Density Function and Mode
- Parzen-Window Network Intrusion Detectors
- Anomaly Detection in Large Graphs
- MAFIA (Maximal Frequent Itemset Mining)
- Neighborhood Formation and Anomaly Detection in Bipartite Graphs
- Anomaly Detection Applet
Books/Book Chapters
- kmeans algorithm http://nlp.stanford.edu/IR-book/html/.../k-means-1.html#sec:kmeans
- Scoring Term, Weighting, vector space model http://nlp.stanford.edu/IR-book/pdf/06vect.pdf...
- Data Mining Book http://www-users.cs.umn.edu/~kumar/dm.../index.php
- Mining Massive Datasets http://i.stanford.edu/~ullman/mmds/booka.pdf...
- Dimensionality Reduction http://www.stat.cmu.edu/~cshalizi/490.../pca-handout.pdf
Tutorials
- Data Mining / Machine Learning Tutorial
- Kernel Density Estimate
- MAFIA (Maximal Frequent Itemset Mining)