Conferences related to Data Mining

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2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.


2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).


2019 IEEE AUTOTESTCON

AUTOTESTCON is the world’s premier conference that brings together themilitary/aerospace automatic test industry and government/military acquirers and usersto share new technologies, discuss innovative applications, and exhibit products andservices.

  • 2018 IEEE AUTOTESTCON

    AUTOTESTCON is the world’s premier conference that brings together the military/aerospace automatic test industry and government/military acquirers and users to share new technologies, discuss innovative applications, and exhibit products and services

  • 2017 IEEE AUTOTESTCON

    IEEE AUTOTESTCON is also known as the Systems Readiness Technology Conference. This major conference and exposition provides focus on the maintenance aspects of systems readiness and providing Mission Assurance through Advanced ATE (Automatic Test Equpmenrt/Systems). This includes Maintenance Repair & Overhaul as well as factory and development automated test equipment. This conference brings military and aerospace industry principals together to share new concepts, technologies and applications in this essential field of supportability and sustainability. The conference includes a major exhibit of exciting new products from a wide variety of exhibitors, and provides the opportunity to meet with senior military and aerospace leaders to discuss their future needs and expectations and the ways in which we can satisfy those needs.

  • 2016 IEEE AUTOTESTCON

    echnical Interchange Meeting for military/aerospace automatic test industry together to share new technologies, discuss innovative applications, and exhibit products and services

  • 2015 IEEE AUTOTESTCON

    IEEE AUTOTEST is an annual Technical Interchange Meeting sponsored by the Institute of Electrical and Electronic Engineers (IEEE). This event serves to gather the military/aerospace automatic test industry together to share new technologies, discuss innovative applications, and exhibit products and services

  • 2014 IEEE AUTOTEST

    IEEE AUTOTESTCON is the world s only conference that focuses primarily on Automated Test and related technology for military, government and aerospace applications. The conference also has an expanded focus into commercial areas that share a common technical base, including aerospace, vehicle and automotive, and commercial factory test applications. Autotestcon provides a unique opportunity to discuss platform support requirements with all DoD Branches, provides hands-on experience with test equipment, and

  • 2013 IEEE AUTOTESTCON

    Content focused on automatic test systems for US military systems.

  • 2012 IEEE AUTOTESTCON

    Automated Test Systems (ATE) and related technologies such as Test Program Sets for US military and defense equipment

  • 2011 IEEE AUTOTESTCON

    Annual conference of the automatic testing industry.

  • 2010 IEEE AUTOTESTCON

    IEEE AUTOTESTCON, The Support Systems Technology Conference, is the largest conference focused on automatic test systems for military and aerospace systems, and has been held annually since 1965. It features more than 120 quality application-focused papers and 250 Exhibits. Attendance ranges between 650 and 750 registered professionals.

  • 2009 IEEE AUTOTESTCON

    Automated Test, Test Technology, and related Support Systems for Defense Systems.

  • 2008 IEEE AUTOTESTCON

    All theoretical and application aspects for an appropriate topic dealing with system readiness, in general, and automatic test technology, in particular. In keeping with our conference theme "Surpassing the Limits-Forging Ahead" our focus will be on new ideas and concepts, unusual testing solutions, and future technologies, e.g. ATE Architectures, Artificial Intelligence in Test, ATE/TPS Development Techniques, ATE/TPS Management, BIT/BIST

  • 2007 IEEE AUTOTESTCON

  • 2006 IEEE AUTOTESTCON

  • 2005 IEEE AUTOTESTCON

  • 2004 IEEE AUTOTESTCON

  • 2003 IEEE AUTOTESTCON

  • 2002 IEEE AUTOTESTCON

  • 2001 IEEE AUTOTESTCON

  • 2000 IEEE AUTOTESTCON

  • AUTOTESTCON '99

  • AUTOTESTCON '98

  • AUTOTESTCON '97

  • AUTOTESTCON '96


2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

International Geosicence and Remote Sensing Symposium (IGARSS) is the annual conference sponsored by the IEEE Geoscience and Remote Sensing Society (IEEE GRSS), which is also the flagship event of the society. The topics of IGARSS cover a wide variety of the research on the theory, techniques, and applications of remote sensing in geoscience, which includes: the fundamentals of the interactions electromagnetic waves with environment and target to be observed; the techniques and implementation of remote sensing for imaging and sounding; the analysis, processing and information technology of remote sensing data; the applications of remote sensing in different aspects of earth science; the missions and projects of earth observation satellites and airborne and ground based campaigns. The theme of IGARSS 2019 is “Enviroment and Disasters”, and some emphases will be given on related special topics.


2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC)

IEEE CCNC 2018 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions


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Periodicals related to Data Mining

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Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Electron Device Letters, IEEE

Publishes original and significant contributions relating to the theory, design, performance and reliability of electron devices, including optoelectronic devices, nanoscale devices, solid-state devices, integrated electronic devices, energy sources, power devices, displays, sensors, electro-mechanical devices, quantum devices and electron tubes.


Electron Devices, IEEE Transactions on

Publishes original and significant contributions relating to the theory, design, performance and reliability of electron devices, including optoelectronics devices, nanoscale devices, solid-state devices, integrated electronic devices, energy sources, power devices, displays, sensors, electro-mechanical devices, quantum devices and electron tubes.


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Most published Xplore authors for Data Mining

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Xplore Articles related to Data Mining

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Spatial and Spatio-temporal Data Mining

2010 IEEE International Conference on Data Mining, 2010

Summary form only given. The recent advances and price reduction of technologies for collecting spatial and spatio-temporal data like Satellite Images, Cellular Phones, Sensor Networks, and GPS devices has facilitated the collection of data referenced in space and time. These huge collections of data often hide interesting information which conventional systems and classical data mining techniques are unable to discover. ...


Application of data mining in traffic management: Case of city of Isfahan

2010 2nd International Conference on Electronic Computer Technology, 2010

This paper describes the work investigating the application of data mining tools to aid in the development of traffic signal timing plans. A case study was conducted to illustrate that the use of hierarchical cluster analysis. This approach can be used for designing of a TOD signal control system, since it automatically identifies time-of-day (TOD) intervals using the historical collected ...


Domain Driven Data Mining (D3M)

2008 IEEE International Conference on Data Mining Workshops, 2008

In deploying data mining into the real-world business, we have to cater for business scenarios, organizational factors, user preferences and business needs. However, the current data mining algorithms and tools often stop at the delivery of patterns satisfying expected technical interestingness. Business people are not informed about how and what to do to take over the technical deliverables. The gap ...


CAKE – Classifying, Associating and Knowledge DiscovEry - An Approach for Distributed Data Mining (DDM) Using PArallel Data Mining Agents (PADMAs)

2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, 2008

This paper accentuate an approach of implementing distributed data mining (DDM) using multi-agent system (MAS) technology, and proposes a data mining technique of ldquoCAKErdquo (classifying, associating & knowledge discovery). The architecture is based on centralized parallel data mining agents (PADMAs). Data mining is part of a word, which has been recently introduced known as BI or business intelligence. The need ...


Seventh IEEE International Conference on Data Mining Workshops - Title

Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007), 2007

The following topics are dealt with: data mining in Web 2.0 environment; knowledge-discovery from multimedia data and multimedia applications; mining and management of biological data; data mining in medicine; optimization-based data mining techniques; high performance data mining; mining graphs and complex structures; data mining on uncertain data; data streaming mining and management; spatial and spatio-temporal data mining.


More Xplore Articles

Educational Resources on Data Mining

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IEEE-USA E-Books

  • Spatial and Spatio-temporal Data Mining

    Summary form only given. The recent advances and price reduction of technologies for collecting spatial and spatio-temporal data like Satellite Images, Cellular Phones, Sensor Networks, and GPS devices has facilitated the collection of data referenced in space and time. These huge collections of data often hide interesting information which conventional systems and classical data mining techniques are unable to discover. Spatial and spatio- temporal data are embedded in continuous space, whereas classical datasets (e.g. transactions) are often discrete. Spatial and spatio-temporal data require complex data preprocessing, transformation, data mining, and post- processing techniques to extract novel, useful, and understandable patterns. The importance of spatial and spatio-temporal data mining is growing with the increasing incidence and importance of large geo-spatial datasets such as maps, repositories of remote-sensing images, trajectories of moving objects generated by mobile devices, etc. Applications include Mobile-commerce industry (location-based services), climatologically effects of El Nino, land- use classification and global change using satellite imagery, finding crime hot spots, local instability in traffic, migration of birds, fishing control, pedestrian behavior analysis, and so on. Thus, new methods are needed to analyze spatial and spatio-temporal data to extract interesting, useful, and non-trivial patterns. The main goal of this tutorial is to disseminate this research field, giving an overview of the current state of the art and the main methodologies and algorithms for spatial and spatio-temporal data mining. This tutorial is directed to researches and practitioners, experts in data mining, analysts of spatial and spatio-temporal data, as well as knowledge engineers and domain experts from different application areas.

  • Application of data mining in traffic management: Case of city of Isfahan

    This paper describes the work investigating the application of data mining tools to aid in the development of traffic signal timing plans. A case study was conducted to illustrate that the use of hierarchical cluster analysis. This approach can be used for designing of a TOD signal control system, since it automatically identifies time-of-day (TOD) intervals using the historical collected data. The cluster analysis approach is able to utilize a high- resolution system state definition that takes full advantage of the extensive set of sensors deployed in a traffic signal system and cluster validation supports the hypotheses presented. The results of this research indicate that advanced data mining techniques hold high potential to provide automated signal control techniques.

  • Domain Driven Data Mining (D3M)

    In deploying data mining into the real-world business, we have to cater for business scenarios, organizational factors, user preferences and business needs. However, the current data mining algorithms and tools often stop at the delivery of patterns satisfying expected technical interestingness. Business people are not informed about how and what to do to take over the technical deliverables. The gap between academia and business has seriously affected the widespread employment of advanced data mining techniques in greatly promoting enterprise operational quality and productivity. To narrow down the gap, cater for realworld factors relevant to data mining, and make data mining workable in supporting decision-making actions in the real world, we propose the methodology of domain driven data mining (D<sup>3</sup>M for short). D<sup>3</sup>M aims to construct next-generation methodologies, techniques and tools for a possible paradigm shift from data-centered hidden pattern mining to domain-driven actionable knowledge delivery. In this talk, we address the concept map of D<sup>3</sup>M, theoretical underpinnings, several general and flexible frameworks, research issues, possible directions, application areas etc. related to D<sup>3</sup>M. Real-world case studies in financial data mining and social security mining are demonstrated to show the effectiveness and applicability of D<sup>3</sup>M in both research and development of real- world challenging problems.

  • CAKE – Classifying, Associating and Knowledge DiscovEry - An Approach for Distributed Data Mining (DDM) Using PArallel Data Mining Agents (PADMAs)

    This paper accentuate an approach of implementing distributed data mining (DDM) using multi-agent system (MAS) technology, and proposes a data mining technique of ldquoCAKErdquo (classifying, associating & knowledge discovery). The architecture is based on centralized parallel data mining agents (PADMAs). Data mining is part of a word, which has been recently introduced known as BI or business intelligence. The need is to derive knowledge out of the abstract data. The process is difficult, complex, time consuming and resource starving. These highlighted problems addressed in the proposed model. The model architecture is distributed, uses knowledge-driven mining technique and flexible enough to work on any data warehouse, which will help to overcome these problems. Good knowledge of data, meta-data and business domain is required for defining rules for data mining. Taking into consideration that the data and data warehouse has already gone through the necessary processes and ready for data mining.

  • Seventh IEEE International Conference on Data Mining Workshops - Title

    The following topics are dealt with: data mining in Web 2.0 environment; knowledge-discovery from multimedia data and multimedia applications; mining and management of biological data; data mining in medicine; optimization-based data mining techniques; high performance data mining; mining graphs and complex structures; data mining on uncertain data; data streaming mining and management; spatial and spatio-temporal data mining.

  • Developing an Integrated Time-Series Data Mining Environment for Medical Data Mining

    In this paper, we present an integrated time-series data mining environment for medical data mining. Medical time-series data mining is one of key issues to get useful clinical knowledge from medical databases. However, users often face difficulties during such medical time-series data mining process for data preprocessing method selection/construction, mining algorithm selection, and post-processing to refine the data mining process as shown in other data mining processes. To get more valuable rules for medical experts from a time- series data mining process, we have designed an environment which integrates time- series pattern extraction methods, rule induction methods and rule evaluation methods with visual human-system interface. After implementing this environment, we have done a case study to mine time- series rules from blood/urine biochemical test database on chronic hepatitis patients. The result shows the availability to find out valuable clinical course rules based on time-series pattern extraction. Furthermore, we compared the difference of time-series pattern extraction methods with objective rule evaluation results.

  • Bibliometric Analysis of Data Mining in the Chinese Social Science Circle

    In this paper, papers about data mining recorded by CSSCI (1998~2007) are collected and analyzed with statistical analysis and bibliometric analysis such as year distribution, journal distribution, subject distribution, the core author and the geographical distribution of the author. So we can identify the core author, core journals, research institutes and the law of research on data mining in the Chinese social science circle, and reveal the review of data mining study and the main theme in the Chinese social science circle. In collusion, this paper indicates some problems and trends about study on data mining.

  • i-Analyst: An Agent-Based Distributed Data Mining Platform

    User-friendliness and performance are important properties of data mining and analysis tools. In this demo, we introduced an agent-based distributed data mining platform that allows users to manage and share the data-mining-related resources conveniently. Furthermore, the platform employs agents for workflow enactment in which the performance is improved with agent abilities. We also present an example to illustrate how the platform works in distributed environment. The performance is relatively competitive with non-agent approach when data is highly distributed and large.

  • Application of Data Mining in Higher Secondary Directorate of Kerala

    In this paper, we discuss Data Mining and its application in Higher Secondary Directorate of Kerala. Data Mining process has a set of functionalities among which classification has wide application in real world data processing. We examine the Naïve Bayes classification techniques. In the third section, we explain Naïve Bayes Theorem using an experiment. This experiment covers attributes like School Type, Candidate Type, Study Type, Districts, etc. These attribute values, we are using to analysing the result of Higher Secondary First Year Improvement Examination held in September 2015. This will improve the performance and data processing speed of Higher Education Directorate. This paper demonstrates the application of Data Mining in Higher Secondary Examination result. This will help further research and will improvise the activity of Higher Secondary Directorate.

  • Research of GIS-based Spatial Data Mining Model

    In this paper, the theories of spatial data mining and geographic information system are described firstly, and the integration model of the spatial data mining is also researched and analyzed in-depth. On the basis of this, a new GIS system structure based on the spatial data mining is presented, which has the advantages of good universality, interaction and easy realization comparing with other structures.



Standards related to Data Mining

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No standards are currently tagged "Data Mining"