Results 251 to 260 of about 24,371,806 (309)

Soil contamination assessment of a 19th-century abandoned Sb-Au mine in northern Portugal. [PDF]

Environ Geochem Health
Resta G, Santos P, Monteiro M, Melo R, Carvalho M, Carvalho A, Lima A, Font E, Ribeiro JA, Azenha M, Adatte T, Flores D.   +11 more
europepmc   +1 more source

<i>Desulfosporosinus</i> and <i>Acididesulfobacillus</i> dominate an acidophilic sulfate-reducing bacteria consortium during acid mine drainage bioremediation. [PDF]

Appl Environ Microbiol
Valdez-Nuñez LF, Chávez IJ, Sekerci F, Ayala-Muñoz D, Straub D, Kappler A, Fischer S, Mansor M.   +7 more
europepmc   +1 more source

Mining Frequent Item sets in Data Streams [PDF]

Dass, Rajanish
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Mining Positional Data Streams

2015
We study frequent pattern mining from positional data streams. Existing approaches require discretised data to identify atomic events and are not applicable in our continuous setting. We propose an efficient trajectory-based preprocessing to identify similar movements and a distributed pattern mining algorithm to identify frequent trajectories.
Jens Haase, Ulf Brefeld
openaire   +1 more source

Processing and mining complex data streams

Information Sciences, 2014
Data mining aims at discovering valid, novel and potentially useful patterns from data. Over last two decades, data mining and the related, older discipline of machine learning have shown tremendous progress and become ones of the main sub-fields of computer science.
Jerzy Stefanowski, Alfredo Cuzzocrea, Dominik Slezak   +2 more
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Advances in data stream mining

WIREs Data Mining and Knowledge Discovery, 2011
AbstractMining data streams has been a focal point of research interest over the past decade. Hardware and software advances have contributed to the significance of this area of research by introducing faster than ever data generation. This rapidly generated data has been termed as data streams. Credit card transactions, Google searches, phone calls in
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Data Stream Mining

2009
Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization.
Gaber, M., Zaslavsky, A., Krishnaswamy, S.   +2 more
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Mining Data Streams

2009
When a space shuttle takes off, tiny sensors measure thousands of data points every fraction of a second, pertaining to a variety of attributes like temperature, acceleration, pressure and velocity. A data gathering server at a networking company receives terabytes of data a day from various network elements like routers, reporting on traffic ...
Tamraparni Dasu, Gary Weiss
openaire   +1 more source