DynamicWEB: Adapting to Concept Drift and Object Drift in COBWEB

Scanlan, Joel; Hartnett, JS; Williams, RN

doi:10.1007/978-3-540-89378-3_46

Cited by 6 publications

(5 citation statements)

References 5 publications

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“…Once an IP was blocked across the gateways it was shown that they would quickly cease their activ ities as shown in Figure3b . This wo rk and its results are discussed at more length in [11].…”

Section: Sharing Information Across Gatewaysmentioning

confidence: 95%

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DynamicWEB: A Method for Reconnaissance Activity Profiling

Scanlan

Hartnett

Williams

2008

2008 IEEE International Symposium on Parallel and Distributed Processing With Applications

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Port scan correlation aims to differentiate between benign and malicious scans. In this paper we will examine a new method of profiling port scan activity in an attempt to lin k d ifferent source IP addresses to being the same end user. A data mining approach DynamicW EB based upon the COBW EB conceptual clustering algorith m is shown along with some preliminary results of it functioning within the context of scan correlation.

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Section: Sharing Information Across Gatewaysmentioning

confidence: 95%

“…It is because of these that detection can occur, and why contextual clustering methods can be of use within security. A full algorith m description of COBW EB is not given here but can be found in Fishers publications [20,21] and also in publications by the authors this paper [22,11].…”

Section: Conceptual Clusteringmentioning

confidence: 99%

DynamicWEB: A Method for Reconnaissance Activity Profiling

Scanlan

Hartnett

Williams

2008

2008 IEEE International Symposium on Parallel and Distributed Processing With Applications

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“…Large part of personal assistance applications are related to handling textual data, example tasks include news story classification [74,4], or document categorization [49,59]. In web search, detecting changes in user satisfaction has been [67,16,9] library, media search [35,22] customer segmentation customer segmentation, [14,5,47,66] profiling Marketing recommender systems movie recommendations [45,18] Management project management software project mgmt. [20] archiving article, mail organization [76,43] recognized to be important [42].…”

Section: Information Managementmentioning

confidence: 99%

“…Personal assistance tasks relate to other types of data, such as networked multimedia, music, video, as well as digital libraries [35]. Large body of applications relate to web personalization and dynamics [67,16,9], where interim system data (logs) is mined.…”

Section: Information Managementmentioning

confidence: 99%

An Overview of Concept Drift Applications

Žliobaitė

Pechenizkiy

Gama

2015

Studies in Big Data

261

188

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In most challenging data analysis applications, data evolve over time and must be analyzed in near real time. Patterns and relations in such data often evolve over time, thus, models built for analyzing such data quickly become obsolete over time. In machine learning and data mining this phenomenon is referred to as concept drift. The objective is to deploy models that would diagnose themselves and adapt to changing data over time. This chapter provides an application oriented view towards concept drift research, with a focus on supervised learning tasks. First we overview and categorize application tasks for which the problem of concept drift is particularly relevant. Then we construct a reference framework for positioning application tasks within a spectrum of problems related to concept drift. Finally, we discuss some promising research directions from the application perspective, and present recommendations for application driven concept drift research and development.

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“…There is also a large body of research addressing web personalization and dynamics [158,135,33,23], which is again subject to drifting user interests. In contrast to end user text mining discussed before, here mostly interim system data (logs) is mined.…”

Section: Personal Assistancementioning

confidence: 99%