Results 221 to 230 of about 938,194 (261)

High Utilizers of Psychiatric Emergency Services

Psychiatric Services, 2005
The purpose of this study was to examine the sociodemographic and clinical characteristics of high utilizers of psychiatric emergency services.Data were collected over four years for 761 patients who were identified as high utilizers according to three definitions (two standard deviations above the mean number of visits to an urban psychiatric ...
Jagoda, Pasic, Joan, Russo, Peter, Roy-Byrne   +2 more
openaire   +2 more sources

Heterogeneous k-anonymization with high utility

2015 IEEE International Conference on Big Data (Big Data), 2015
Heterogeneous k-anonymization with high ...
Doka, Katerina, Xue, Mingqiang, Tsoumakos, Dimitrios, Karras, Panagiotis, CUZZOCREA, Alfredo Massimiliano, Koziris, Nectarios   +5 more
openaire   +3 more sources

The DOGMA approach to high-utilization supercomputing

Proceedings. The Seventh International Symposium on High Performance Distributed Computing (Cat. No.98TB100244), 2002
Heterogeneous distributed computing has traditionally been a problematic undertaking which increases in complexity as heterogeneity increases. The recent advent of Java has made heterogeneous computing a fairly straightforward task. Nevertheless, many researchers have not considered the use of Java in a mainstream parallel programming environment.
Glenn Judd, Mark J. Clement, Quinn Snell
openaire   +1 more source

A Visualizer for High Utility Itemset Mining

2014 IEEE 17th International Conference on Computational Science and Engineering, 2014
Mining high utility item sets is one of the most important research issues in data mining owing to its ability to consider nonbinary frequency values of items in transactions and different profit values for each item. Although several studies have been carried out, current methods present the mined results in the form of textual lists for users, which ...
Wei Song 0004, Mingyuan Liu
openaire   +1 more source

Mining summarization of high utility itemsets

Knowledge-Based Systems, 2015
Mining interesting itemsets from transaction databases has attracted a lot of research interests for decades. In recent years, high utility itemset (HUI) has emerged as a hot topic in this field. In real applications, the bottleneck of HUI mining is not at the efficiency but at the interpretability, due to the huge number of itemsets generated by the ...
Xiong Zhang, Zhi-Hong Deng 0001
openaire   +1 more source

Mining Discriminative High Utility Patterns

2016
Recently, many approaches for high utility pattern mining (HUPM) have been proposed, but most of them aim at mining high-utility patterns (HUPs) instead of frequent ones. The major drawback is that any combination of a low-utility item with a very high utility pattern is regarded as a HUP, even if this combination is infrequent and contains items that ...
Jerry Chun-Wei Lin, Wensheng Gan, Philippe Fournier-Viger, Tzung-Pei Hong   +3 more
openaire   +1 more source

Vertical mining for high utility itemsets

2012 IEEE International Conference on Granular Computing, 2012
Recently, high utility itemsets mining becomes one of the most important research issues in data mining due to its ability to consider different profit values for every item. In the past studies, most algorithms generate high utility itemsets from a set of transactions in horizontal data format.
Wei Song 0004, Yu Liu, Jinhong Li
openaire   +1 more source

Mining High Utility Subgraphs

2021 International Conference on Data Mining Workshops (ICDMW), 2021
Md. Tanvir Alam, Amit Roy, Chowdhury Farhan Ahmed, Md. Ashraful Islam 0001, Carson K. Leung   +4 more
openaire   +1 more source

Diffix: High-Utility Database Anonymization

2017
In spite of the tremendous privacy and liability benefits of anonymization, most shared data today is only pseudonymized. The reason is simple: there haven’t been any anonymization technologies that are general purpose, easy to use, and preserve data quality.
Francis, P., Probst Eide, S., Munz, R.
openaire   +2 more sources

Mining Minimal High-Utility Itemsets

2016
Mining high-utility itemsets HUIs is a key data mining task. It consists of discovering groups of items that yield a high profit in transaction databases. A major drawback of traditional high-utility itemset mining algorithms is that they can return a large number of HUIs. Analyzing a large result set can be very time-consuming for users.
Philippe Fournier-Viger, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, Usef Faghihi   +4 more
openaire   +1 more source