Multi-agent technology for distributed data mining and classification

Gorodetsky, Vladimir; Karsaeyv, O.; Samoilov, V. V.

doi:10.1109/iat.2003.1241116

Cited by 30 publications

(26 citation statements)

References 3 publications

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“…They addressed as a key problem the fact that data sources are distributed, heterogeneous and, as a rule, of large scale [14]. In addition, the authors addressed as an issue that the Distributed Data Mining MAS design technology presumes collaborative activities of agentmediated distributed users [14]. Therefore, they proposed an architecture of DDM and DC MASs and a technology for their design.…”

Section: Jadementioning

confidence: 99%

“…Therefore, they proposed an architecture of DDM and DC MASs and a technology for their design. They further proposed a number of well-developed protocols supporting agent-mediated design of applied DDM and DC MASs [14].…”

Section: Jadementioning

confidence: 99%

“…For instance, in [14], the authors proposed a MAS Technology for Distributed Data Mining (DDM) and Distributed Classification (DC). They addressed as a key problem the fact that data sources are distributed, heterogeneous and, as a rule, of large scale [14]. In addition, the authors addressed as an issue that the Distributed Data Mining MAS design technology presumes collaborative activities of agentmediated distributed users [14].…”

Section: Jadementioning

confidence: 99%

“…RELATED WORK Some approaches proposed [12,8,14] perform the data mining process by using Multi-Agent Systems. For instance, in [14], the authors proposed a MAS Technology for Distributed Data Mining (DDM) and Distributed Classification (DC). They addressed as a key problem the fact that data sources are distributed, heterogeneous and, as a rule, of large scale [14].…”

Section: Jadementioning

confidence: 99%

See 3 more Smart Citations

Generating Software Agents for Data Mining: An Example for the Health Data Area

Morejon

Viana

Lucena

2017

International Conferences on Software Engineering and Knowledge Engineering

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Abstract-Data mining has been a hot topic that attracts both database and machine learning researchers. Due to the constant growth of data volume there is an increasing need to obtain knowledge from these large data sets that are very difficult to handle and process with traditional methods. Software agents can play a significant role performing data mining processes in ways that are more efficient. For instance, they can work to perform selection, extraction, preprocessing and integration of data as well as parallel, distributed, or multisource mining. This paper proposes a framework based on multi-agent systems to apply data mining techniques to health data sets. For a first usage scenario, we use a data set for hypothyroidism and run two mining processes in parallel.

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Section: Jadementioning

confidence: 99%

Section: Jadementioning

confidence: 99%

Section: Jadementioning

confidence: 99%

Section: Jadementioning

confidence: 99%

See 2 more Smart Citations

Generating Software Agents for Data Mining: An Example for the Health Data Area

Morejon

Viana

Lucena

2017

International Conferences on Software Engineering and Knowledge Engineering

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“…This software tool was the subject of research during last years and the current version is the third one. Previous versions of MASDK [13] were used for rapid prototyping of different MAS applications [14,15]. The experience accumulated so far allowed understanding of the drawbacks and limitations of the previous two versions of MASDK and developing adequate requirements to its current version, 3.0.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent System Development Kit

Gorodetski

Karsaev

Samoilov

et al. 2005

Intelligent Information Processing II

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Abstract:Recent research in area of multi-agent technology attracted a growing attention of both scientific community and industrial companies. This attention is stipulated by powerful capabilities of multi-agent technology allowing to create large scale distributed intelligent systems, and, on the other hand, by practical needs of industrial companies to possess an advanced and reliable technology for solving of practically important problems. Currently one of the topmost questions of the research is development of powerful methodologies for engineering of agent-based systems and development of more effective and efficient tools supporting implementation of applied systems. The paper presents one of such tools, Multi Agent System Development Kit, based on and implementing of Gaia methodology. It supports the whole life cycle of multi-agent system development and maintains integrity of solutions produced at different stages of the development process.

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Actionable knowledge discovery and delivery

Cao

2012

WIREs Data Min & Knowl

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Actionable knowledge has been qualitatively and intensively studied in the social sciences. Its marriage with data mining is only a recent story. On the one hand, data mining has been booming for a while and has attracted an increasing variety of increasing applications. On the other, it is a reality that the so‐called knowledge discovered from data by following the classic frameworks often cannot support meaningful decision‐making actions. This shows the poor relationship and significant gap between data mining research and practice, and between knowledge, power, and action, and forms an increasing imbalance between research outcomes and business needs. Thorough and innovative retrospection and thinking are timely in bridging the gaps and promoting data mining toward next‐generation research and development: namely, the paradigm shift from knowledge discovery from data to actionable knowledge discovery and delivery. © 2012 Wiley Periodicals, Inc. This article is categorized under: Application Areas > Data Mining Software Tools Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining

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Multi-agent technology for distributed data mining and classification

Cited by 30 publications

References 3 publications

Generating Software Agents for Data Mining: An Example for the Health Data Area

Generating Software Agents for Data Mining: An Example for the Health Data Area

Multi-Agent System Development Kit

Actionable knowledge discovery and delivery

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