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2014 IEEE International Symposium on Parallel & Distributed Processing Symposium (IPDPS)
IPDPS is an international forum for engineers and scientists from around the world to present their latest research findings in all aspects of parallel computation.
2013 IEEE 11th International Conference on Industrial Informatics (INDIN)
The aim of the conference is to bring together researchers and practitioners from industry and academia and provide them with a platform to report on recent developments, deployments, technology trends and research results, as well as initiatives related to industrial informatics and their application.
2013 IEEE 14th International Conference on Information Reuse & Integration (IRI)
Information reuse and integration (IRI) seeks to maximally exploit available digital information to create new knowledge and to reuse it for addressing newer challenges.
2012 4th Conference on Data Mining and Optimization (DMO)
The scope of the conference includes, but is not limited to the following subjects: Parallel and distributed data mining algorithms, Data streams mining, Graph mining, Spatial data mining, Text & multimedia mining, Web mining, Pre-processing techniques, etc. Linear/Nonlinear Optimization, Integer/Combinatorial Optimization, metaheuristics, Network Optimization, Scheduling Problems and Stochastic Optimization.
Sensor Technology Nonlinear Circuits & Systems Signal Processing Instrumentation & Control Systems Communications Systems Image Processing & Multimedia Systems Biomedical Systems VLSI & Embedded Systems Power Electronics & Power Systems Computational & Articial Intelligence
Gao Qiang; Wang Xinmin; Dong Chao; Li Chenguang Computer Application and System Modeling (ICCASM), 2010 International Conference on, 2010
The water quality data in some petrochemical company are stored in the lims database, in order to support the field operation's decision-making according to these data, it's necessary to do some appropriate data mining. However, the accuracy of the results of data mining directly associated with the quality of source data, so data preprocessing on the raw data is necessary ...
Xishui Pan; Xuezhong Zhou; Hongmei Song; Runshun Zhang; Tingting Zhang e-Health Networking, Applications and Services (Healthcom), 2012 IEEE 14th International Conference on, 2012
Clinical data warehouse has been developed as a fundamental data infrastructure for large scale TCM clinical data management and decision support services. However, as a key component, data extraction, transforming and loading (ETL) is a complicated and labor intensive task to ensure high data quality before all kinds of data analyses. This paper introduces an enhanced ETL technique framework, which ...
Bakar, A.A.; Othman, Z.A.; Mohd Shuib, Nor Liyana Data Mining and Optimization, 2009. DMO '09. 2nd Conference on, 2009
Data preprocessing is an important step in data mining. It is used to resolve various types of problem in a large dataset in order to produce quality data. It consists of four steps, namely, data cleaning, integration, reduction and transformation. The literature shows that each preprocessing step consists of various techniques. In order to develop quality data, a data miner ...
Pirenne, B.; Guillemot, E. Oceans, 2012, 2012
The advent of large scale, high-bandwidth on-line access and generously powered ocean floor observatories were predicted to transform the way ocean science is conducted. They have lived up to this promise. New cabled observatories have sometimes in excess of 100 different instruments semipermanently installed in areas of scientific interest. The instruments represent hundreds of different variables measured at a high ...
Othman, Z.A.; Bakar, A.A.; Hamdan, A.R.; Omar, K.; Mohd Shuib, Nor Liyana Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on, 2007
The current data mining tools is used to build knowledge based on a huge historical data. At present, businesses are facing with fast growing data that are very valuable in contributing knowledge. Knowledge should be updated regularly in order to ensure its quality and precision thus improve the decision making process. Data mining has shown great potential in extracting valuable ...
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