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Mining Frequent Patterns from Very High Dimensional Data - SIAM
This kind of very high dimensional data needs data mining techniques to discover interesting knowledge from it. For example, frequent pattern mining algorithm ...

Top-Down Mining of Interesting Patterns from Very High
Top-Down Mining of Frequent Patterns from Very High Dimensional Data. Hongyan Liu†. Jiawei Han‡. Dong Xin‡. Zheng Shao‡. †Department of Management ...

Mining high dimensional data - UCLA Computer Science
dimensionality. Key words: High-dimensional data mining, frequent pattern, clustering high-dimensional ... a dimension. Researchers and practitioners are very eager in analyzing these .... FARMER: finding interesting rule groups in microarray ...

Compression, Clustering and Pattern Discovery in Very High
Very High Dimensional Discrete-Attribute Datasets ... interesting patterns. ... SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2003).

Frequent pattern mining - UCSB Computer Science
itemsets from very high dimensional data sets and mining very long patterns ... an interesting downward closure property, called Apriori, among frequent k-.

Efficient Algorithms for Clustering and Classifying High Dimensional
Efficient Algorithms for Clustering and Classifying High Dimensional Text and. Discretized Data ... Recent advances in data mining allow for exploiting patterns as the primary means ... In our second contribution, we introduce the notion of closed interesting itemsets, ... of parameter values, even on highly correlated datasets.

Mining Closed and Multi-Supports-Based Sequential Pattern in High
Aug 17, 2014 ... mining of sequential patterns in high dimensional dataset. TD-Seq [11] is ... some interesting patterns which appear more than once in a sequence. 2.1. .... extension item and no super sequence of α, then output α as a closed ...

Frequent Pattern Mining Algorithms for Data Clustering - Exploratory
tering algorithms that can handle high-dimensional data. .... An extension of the Apriori idea for very large itemsets has been termed 'colossal patterns' [82]. ..... Another interesting connection to frequent pattern mining is discussed with the.

Closed Sequential Pattern Mining in High Dimensional Sequences
Index Terms—sequential pattern mining; high dimensional sequence ... interesting closed patterns. ... frequent in S and there exists no super pattern Y such that.

PaMPa-HD: a Parallel MapReduce-based frequent Pattern miner for
frequent closed itemset mining algorithm for high-dimensional datasets, based on ... exist to address very long transactions, such as Carpenter [3], and no distributed ..... examples of interesting high-dimensional dataset are URL reputation ...

Fast Mining of High Dimensional Expressive Contrast Patterns
Patterns of contrast are a very important way of comparing multi- dimensional ... technique for mining contrast patterns in high dimensional space. It is able to mine ... interesting alternative to popular structures such as the fre- quent pattern tree ...

Searching and Mining High Dimensional Data - School of Computing
Data Mining: Foundation, Techniques and Applications ... Finding Patterns in Extremely High Dimensional Data ..... uncertain attributes will be interesting.

Mining Low-Support Discriminative Patterns from Dense and High
However, for dense and high-dimensional data sets, they have to use high thresholds to produce the complete ... limited time, and thus, may miss interesting low-support patterns. .... proaches can work even with a very low minsup threshold.

An Iterative Strategy for Pattern Discovery in High-dimensional Data
data-mining approaches have been proposed which cluster or group ... Pattern discovery of target objects presents interesting but also very challenging problems. .... pattern-discovery strategy for high dimensional data sets, which consists of ...

Relevant Subspace Clustering: Mining the Most Interesting Non
Keywords-data mining; high dimensional data; subspace clustering; redundancy ... However, patterns occur in multiple projections of the data. Subspace clustering ..... the cluster is very high, i.e. the cluster is not interesting. High cost k( O, ...

Mining Strong Affinity Association Patterns in Data Sets - Hui Xiong
finding patterns in dense data sets even at very low support thresholds, where most of ... patterns also show great promise for clustering items in high dimensional space. ... interesting patterns involving items with substantially different support ...

Rare Event Analysis of High Dimensional Building - Purdue e-Pubs
atypical building operating patterns, detect and diagnose faults, and ... Keywords: rare event analysis; data mining; building automation; clustering analysis; outlier ... massive data sets, as it specifically focuses on the events which are very ... Therefore, rare event analysis of the high dimensional BAS data helps to identify.

Outlier Detection for High Dimensional Data - Charu Aggarwal
Two interesting algorithms 22,. 25 define .... be computationally efficient for very high dimensional ... and mine those patterns for which randomness cannot jus-.

Subspace Search and Visualization to Make Sense of Alternative
The analysis of high-dimensional (HD) data is an ubiquitously rel- evant, yet notoriously ... interesting patterns may often be located only in subspace projec- tions of the data. ... Visual Analytics in the context of automated mining algorithms . It furthermore ... subspace clustering approaches do not scale well for very HD data.

Review on Extraction of Intelligence from Higher Order Mining
Investigating the mined interesting rules and the utility of mining rules from the results ... Key words: Data Mining and Algorithms Artificial Intelligence Big Data High Dimensional Data .... produces interesting patterns then it is highly desirable &.

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