Conferences related to Data Mining

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2019 20th IEEE International Conference on Mobile Data Management (MDM)

The MDM series of conferences, since its debut in 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The conference provides unique opportunities to bring researchers, engineers, and practitioners together to explore new ideas, techniques, and tools, and exchange experiences. Comprising both research and industry tracks, it serves as an important bridge between academic researchers and industry researchers. Along with the presentations of research publications, it also serves as a meeting place for technical demonstrations (demos), workshops, advanced seminars, panel discussions as well as Industrial forum to cater industrial developers.The conference focuses on research contributions in data management in mobile, ubiquitous and pervasive computing.

  • 2018 19th IEEE International Conference on Mobile Data Management (MDM)

    The conference aims to attract original research contributions in the interesection of mobile computing and data management. Topics of interest include, but not limited to:- Mobile Cloud Computing and Data Management - Data Management for Internet of Things (IoT) and Sensor Systems- Data Management for Augmented Reality Systems- Data Management for Intelligent Transportation Systems, Smart Spaces- Mobile Crowd-Sourcing and Crowd-Sensing- Mobile Data Analytics- Behavioural/Activity Sensing and Analytics- Mobile Location-Based Social Networks- Mobile Recommendation Systems- Context-aware Computing for Intelligent Mobile Services- Middleware and Tools for Mobile and Pervasive Computing- Theoretical Foundations of Data-intensive Mobile Computing- Data Stream Processing in Mobile/Sensor Networks- Indexing, Optimisation and Query Processing for Moving Objects/Users- Security and Privacy in Mobile Systems

  • 2017 18th IEEE International Conference on Mobile Data Management (MDM)

    Mobile computing and data management

  • 2016 17th IEEE International Conference on Mobile Data Management (MDM)

    The Mobile Data Management series of conferences first debuted in December 1999. Since inception, it has established itself as a prestigious forum to exchange innovative and significant research results in mobile data management. Comprising both research and industry tracks, it serves as an important bridge between academic researchers and industry researchers. Along with the presentations of research publications, it also serves as a meeting place for technical demonstrations (Demos), workshops, panel discussions as well as PhD forum and Industrial forum to cater PhD students and industrial developers.The conference focuses on research contributions in data management in mobile, ubiquitous and pervasive computing.

  • 2015 16th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2014 15th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility

  • 2013 14th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2012 13th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas, techniques, and tools, and to exchange experiences.

  • 2011 12th IEEE International Conference on Mobile Data Management (MDM)

    The MDM series of conferences, since its debut in December 1999, has established itself as a prestigious forum for the exchange of innovative and significant research results in mobile data management. The term mobile in MDM has been used from the very beginning in a broad sense to encompass all aspects of mobility - aspects related to wireless, portable and tiny devices. The conference provides unique opportunities for researchers, engineers, practitioners, developers, and users to explore new ideas.

  • 2010 11th International Conference on Mobile Data Management (MDM)

    The annual MDM conference is a leading international forum that focuses on data management for mobile, ubiquitous, and pervasive computing. It brings together a wide range of researchers, practitioners, and users to explore scientific and industrial challenges that arise in the areas of data management and mobile computing.

  • 2008 9th International Conference on Mobile Data Management (MDM)

  • 2007 International Conference on Mobile Data Management (MDM)

  • 2006 International Conference on Mobile Data Management (MDM)

  • 2004 IEEE International Conference on Mobile Data Management (MDM)


2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops andinvitedsessions of the latest significant findings and developments in all the major fields ofbiomedical engineering.Submitted papers will be peer reviewed. Accepted high quality paperswill be presented in oral and postersessions, will appear in the Conference Proceedings and willbe indexed in PubMed/MEDLINE & IEEE Xplore


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 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

The IEEE ICCI*CC series is a flagship conference of its field. It not only synergizes theories of modern information science, computer science, communication theories, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software science, knowledge science, cognitive robots, cognitive linguistics, and life science, but also promotes novel applications in cognitive computers, cognitive communications, computational intelligence, cognitive robots, cognitive systems, and the AI, IT, and software industries.

  • 2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Informatics models of the brainCognitive processes of the brainThe cognitive foundation of big dataMachine consciousnessNeuroscience foundations of information processingDenotational mathematics (DM)Cognitive knowledge basesAutonomous machine learningNeural models of memoryInternal information processingCognitive sensors and networksCognitive linguisticsAbstract intelligence (aI)Cognitive information theoryCognitive information fusionCognitive computersCognitive systemsCognitive man-machine communicationCognitive InternetWorld-Wide Wisdoms (WWW+)Mathematical engineering for AICognitive vehicle systems Semantic computingDistributed intelligenceMathematical models of AICognitive signal processingCognitive image processing Artificial neural netsGenetic computingMATLAB models of AIBrain-inspired systemsNeuroinformaticsNeurological foundations of the brainSoftware simulations of the brainBrain-system interfacesNeurocomputingeBrain models

  • 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics is a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Cognitive Computing is a cutting-edge paradigm of intelligent computing methodologies and systems based on CI, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. CI and CC not only synergize theories of modern information science, computer science, communication theories, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software science, knowledge science, cognitive robots, cognitive linguistics, and life science, but also reveal exciting applications in cognitive computers, cognitive robots, and computational intelligence.

  • 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics (CI) is a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence (¿I) theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Cognitive Computing (CC) is a cutting-edge paradigm of intelligent computing methodologies and systems based on cognitive informatics, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain.

  • 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    The scope of the conference covers cognitive informatics, cognitive computing, cognitive communications, computational intelligence, and computational linguitics.

  • 2014 IEEE 13th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics, cognitive computing, cognitive science, cognitive robots, artificial intelligence, computational intelligence

  • 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics (CI) is a cutting-edge and multidisciplinary research field that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software engineering, knowledge engineering, cognitive robots, scientific philosophy, cognitive linguistics, life sciences, and cognitive computing.

  • 2012 11th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 11th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 12) focuses on the theme of e-Brain and Cognitive Computers.

  • 2011 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 10th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 11) focuses on the theme of Cognitive Computers and the e-Brain.

  • 2010 9th IEEE International Conference on Cognitive Informatics (ICCI)

    Cognitive Informatics (CI) is a cutting-edge and transdisciplinary research area that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, neuropsychology, medical science, systems science, software engineering, telecommunications, knowledge engineering, philosophy, linguistics, economics, management science, and life sciences.

  • 2009 8th IEEE International Conference on Cognitive Informatics (ICCI)

    The 8th IEEE International Conference on Cognitive Informatics (ICCI 09) focuses on the theme of Cognitive Computing and Semantic Mining. The objectives of ICCI'09 are to draw attention of researchers, practitioners, and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2008 7th IEEE International Conference on Cognitive Informatics (ICCI)

    The 7th IEEE International Conference on Cognitive Informatics (ICCI 08) focuses on the theme of Cognitive Computers and Computational Intelligence. The objectives of ICCI 08 are to draw attention of researchers, practitioners and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2007 6th IEEE International Conference on Cognitive Informatics (ICCI)

  • 2006 5th IEEE International Conference on Cognitive Informatics (ICCI)

  • 2005 4th IEEE International Conference on Cognitive Informatics (ICCI)


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).


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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"