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Difference between revisions of "References for KDD work"
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== Books/Book Chapters == | == Books/Book Chapters == | ||
| − | * | + | * [http://nlp.stanford.edu/IR-book/html/.../k-means-1.html#sec:kmeans kmeans algorithm] |
| − | * | + | * [http://nlp.stanford.edu/IR-book/pdf/06vect.pdf... Scoring Term, Weighting, vector space model] |
| − | * | + | * [http://www-users.cs.umn.edu/~kumar/dm.../index.php Data Mining Book] |
| − | * | + | * [http://i.stanford.edu/~ullman/mmds/booka.pdf... Mining Massive Datasets] |
| − | * | + | * [http://www.stat.cmu.edu/~cshalizi/490.../pca-handout.pdf Dimensionality Reduction] |
== Tutorials == | == Tutorials == | ||
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== Software == | == Software == | ||
| + | * [http://www.cs.cornell.edu/bigreddata/.../assocMining_main.htm MAFIA (Maximal Frequent Itemset Mining)] | ||
| + | * [http://alumni.cs.ucr.edu/~wli/Anomaly.../AnomalyDetection.html Anomaly Detection Applet] | ||
| + | * [http://gokererdogan.com/files/thesis/ODToolbox.pdf... Outlier Detection Toolbox] | ||
Latest revision as of 12:55, 7 March 2015
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
- Scoring Term, Weighting, vector space model
- Data Mining Book
- Mining Massive Datasets
- Dimensionality Reduction
Tutorials
- Data Mining / Machine Learning Tutorial
- Kernel Density Estimate
- MAFIA (Maximal Frequent Itemset Mining)