Interaction of Agents and Data Mining in Ubiquitous Environment

Gorodetsky, Vladimir; Karsaev, Oleg; Samoylov, Vladimir; Serebryakov, Sergey

doi:10.1109/wiiat.2008.354

Cited by 7 publications

(8 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One example of is given in Gorodetsky et al . (2008) where seven agents communicate asynchronously by message passing according to a protocol and apply a strategic negotiation. cooperation (), when the agents contribute to a common goal. For example in Ghedini Ralha & Sarmento Silva (2012), Haider et al .…”

Section: An Ontology Of Agent Mining Approachesmentioning

confidence: 99%

Agent mining approaches: an ontological view

Strugeon

Oliveira

Zekri

et al. 2021

The Knowledge Engineering Review

View full text Add to dashboard Cite

Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

show abstract

Section: An Ontology Of Agent Mining Approachesmentioning

confidence: 99%

Agent mining approaches: an ontological view

Strugeon

Oliveira

Zekri

et al. 2021

The Knowledge Engineering Review

View full text Add to dashboard Cite

show abstract

“…System usage datasets and streams were mined in order to profile users using various techniques including clustering based methods [35]. Various network connections were mined in order to detect anomalous connections using techniques such as fuzzy-based [36], association rules [37], classification methods [38] etc. Time series concepts were also used to analyze network data.…”

Section: During 2000smentioning

confidence: 99%

“…In Gorodetsky et. al [38], agent technology was used to assist mining processes in a ubiquitous environment.…”

Section: During 2000smentioning

confidence: 99%

“…Desired events related to faults, anomalies and usage [4], [7], [15], [17], [18], [19], [21], [23], [26], [31], [34], [38], [40], [46], [48], [52], [56], [63], [65], [90], [91], [92], [93], [94], [95] Various data mining based approaches for monitoring network and systems events which are desired and related to errors, faults, anomalies and usage. The approaches are mostly based on pattern matching, association, prediction and classification.…”

Section: Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

Four Decades of Data Mining in Network and Systems Management

Kalegele

Sasai

Takahashi

et al. 2015

IEEE Trans. Knowl. Data Eng.

View full text Add to dashboard Cite

How has the interdisciplinary data mining field been practiced in Network and Systems Management (NSM)? In Science and Technology, there is a wide use of data mining in areas like bioinformatics, genetics, Web and more recently astroinformatics. However, the application in NSM has been limited and inconsiderable. In this article, we provide an account of how data mining has been applied in managing networks and systems for the past four decades, presumably since its birth. We look into the field's applications in the key NSM activities -discovery, monitoring, analysis, reporting and domain knowledge acquisition. In the end, we discuss our perspective on the issues that are considered critical for the effective application of data mining in the modern systems which are characterized by heterogeneity and high dynamism.

show abstract

“…1 One may assume that, for every agent in the protection system, the most useful information arrives not only from the agents designed to detect the attacks of the same class and detect anomalies; the information from the agents designed to detect attacks of other classes that have similar indicators can also be useful. To seek such agents, the learning mechanism with self organization can be used (see [18]). We briefly describe it here.…”

Section: Self Organization and Distributed Learningmentioning

confidence: 99%

Self-organization and multiagent systems: II. Applications and the development technology

Городецкий

2012

J. Comput. Syst. Sci. Int.

View full text Add to dashboard Cite

Major trends in the development of modern information technologies are to a large extend determined by important practical problems that arise in economics, ecology, safety of society and individuals, and in other fields. Even though these problems seem to be quite different and the require ments for their software implementation are also different, they have many common features, which imply the most stringent requirements for modern information technologies. These features were ana lyzed in the first part of the present paper. That analysis showed that the new requirements for the model and software implementation of such problems are best met by the multiagent self organizing system model. In this paper, we consider examples of using this model in various applications and describe their architectures and software implementation; in particular, multiagent self organization models as applied for flood forecasting and planning and operational enterprise management are described. New capabilities of multiagent self organizing systems are demonstrated using a self learn ing system for detecting intrusions into computer networks as an example. Here, the problem of self configuration of an overlay network is actually solved. The capabilities of a multiagent self organizing system in large scale control in real time are demonstrated using adaptive traffic control in large cities. For the software implementation of multiagent self organizing systems, special development tools that are different from the existing ones are needed because the conventional top down development par adigm is inappropriate for self organizing architectures. The cause is that the global behavior of a mul tiagent self organizing system emerges due to local interactions; therefore, it cannot be predicted in advance. For that reason, the bottom up development model is more appropriate for such systems. In this paper, we give a brief review of the models and approaches proposed for this purpose. One of the promising approaches based on the use of the so called self organization design patterns is described in more detail. Results of using the multiagent self organization model are discussed and prospects of its practical application are estimated.

show abstract

Interaction of Agents and Data Mining in Ubiquitous Environment

Cited by 7 publications

References 3 publications

Agent mining approaches: an ontological view

Agent mining approaches: an ontological view

Four Decades of Data Mining in Network and Systems Management

Self-organization and multiagent systems: II. Applications and the development technology

Contact Info

Product

Resources

About