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<meta content="Hartnett, Jacky" name="eprints.creators_name" />
<meta content="Williams, Raymond" name="eprints.creators_name" />
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<meta content="Establishing relationships within a dataset is one of the core objectives of data mining. In this paper a method of correlating behaviour profiles in a continuous dataset is presented. The profiling problem which motivated the research is intrusion detection. The profiles are dynamic in nature, changing frequently, and are made up of many attributes. The paper describes a modified version of the COBWEB hierarchical conceptual clustering algorithm called Dynamic WEB. Dynamic WEB operates at runtime, keeping the profiles up to date, and in the correct location within the clustering tree. Further, as there are a number of attributes within the domain of interest, the tree also extends multi-dimensionally. This allows for multiple correlations to occur simultaneously, focussing on different attributes within the one profile." name="eprints.abstract" />
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<meta content="1. Fisher, D.H., Knowledge Acquisition Via Incremental Conceptual Clustering, Mach. Learn., 1987 2 (2) p. 139-172
2. Witten, I. and E.Frank, Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, 2000, San Francisco: Morgan Kaufmann Publishers, 371.
3. Gennari, J.H., P. langley, and D.Fisher, Models of incremental concept formation, Artif. Intell., 1989 40 (1-3): p. 11-61
4. Newman, D.J., et al., (UCI) Repository of machine learning databases. 1998, University of California, Irvine, Dept. of Information and Computer Sciences." name="eprints.referencetext" />
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<meta content="Establishing relationships within a dataset is one of the core objectives of data mining. In this paper a method of correlating behaviour profiles in a continuous dataset is presented. The profiling problem which motivated the research is intrusion detection. The profiles are dynamic in nature, changing frequently, and are made up of many attributes. The paper describes a modified version of the COBWEB hierarchical conceptual clustering algorithm called Dynamic WEB. Dynamic WEB operates at runtime, keeping the profiles up to date, and in the correct location within the clustering tree. Further, as there are a number of attributes within the domain of interest, the tree also extends multi-dimensionally. This allows for multiple correlations to occur simultaneously, focussing on different attributes within the one profile." name="DC.description" />
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<h1 class="ep_tm_pagetitle">Dynamic WEB: Profile correlation using COBWEB</h1>
<p style="margin-bottom: 1em" class="not_ep_block"><span class="person_name">Scanlan, Joel</span> and <span class="person_name">Hartnett, Jacky</span> and <span class="person_name">Williams, Raymond</span> (2006) <xhtml:em>Dynamic WEB: Profile correlation using COBWEB.</xhtml:em> In: 19th Australian Joint Conference on Artificial Intelligence, 4-8 Dec 2006, Hobart.</p><p style="margin-bottom: 1em" class="not_ep_block"></p><table style="margin-bottom: 1em" class="not_ep_block"><tr><td valign="top" style="text-align:center"><a onmouseover="EPJS_ShowPreview( event, 'doc_preview_698' );" href="http://eprints.utas.edu.au/687/1/DynamicWebPaper.pdf" onmouseout="EPJS_HidePreview( event, 'doc_preview_698' );"><img alt="[img]" src="http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png" class="ep_doc_icon" border="0" /></a><div class="ep_preview" id="doc_preview_698"><table><tr><td><img alt="" src="http://eprints.utas.edu.au/687/thumbnails/1/preview.png" class="ep_preview_image" border="0" /><div class="ep_preview_title">Preview</div></td></tr></table></div></td><td valign="top"><a href="http://eprints.utas.edu.au/687/1/DynamicWebPaper.pdf"><span class="ep_document_citation">PDF</span></a> - Requires a PDF viewer<br />139Kb</td></tr></table><div class="not_ep_block"><h2>Abstract</h2><p style="padding-bottom: 16px; text-align: left; margin: 1em auto 0em auto">Establishing relationships within a dataset is one of the core objectives of data mining. In this paper a method of correlating behaviour profiles in a continuous dataset is presented. The profiling problem which motivated the research is intrusion detection. The profiles are dynamic in nature, changing frequently, and are made up of many attributes. The paper describes a modified version of the COBWEB hierarchical conceptual clustering algorithm called Dynamic WEB. Dynamic WEB operates at runtime, keeping the profiles up to date, and in the correct location within the clustering tree. Further, as there are a number of attributes within the domain of interest, the tree also extends multi-dimensionally. This allows for multiple correlations to occur simultaneously, focussing on different attributes within the one profile.</p></div><table style="margin-bottom: 1em" cellpadding="3" class="not_ep_block" border="0"><tr><th valign="top" class="ep_row">Item Type:</th><td valign="top" class="ep_row">Conference or Workshop Item (Paper)</td></tr><tr><th valign="top" class="ep_row">Keywords:</th><td valign="top" class="ep_row">data mining, clustering algorithms, intrusion detection</td></tr><tr><th valign="top" class="ep_row">Subjects:</th><td valign="top" class="ep_row"><a href="http://eprints.utas.edu.au/view/subjects/280207.html">280000 Information, Computing and Communication Sciences > 280200 Artificial Intelligence and Signal and Image Processing > 280207 Pattern Recognition</a></td></tr><tr><th valign="top" class="ep_row">ID Code:</th><td valign="top" class="ep_row">687</td></tr><tr><th valign="top" class="ep_row">Deposited By:</th><td valign="top" class="ep_row"><span class="ep_name_citation"><span class="person_name">Dr Raymond Williams</span></span></td></tr><tr><th valign="top" class="ep_row">Deposited On:</th><td valign="top" class="ep_row">01 Feb 2007</td></tr><tr><th valign="top" class="ep_row">Last Modified:</th><td valign="top" class="ep_row">09 Jan 2008 02:30</td></tr><tr><th valign="top" class="ep_row">ePrint Statistics:</th><td valign="top" class="ep_row"><a target="ePrintStats" href="/es/index.php?action=show_detail_eprint;id=687;">View statistics for this ePrint</a></td></tr></table><p align="right">Repository Staff Only: <a href="http://eprints.utas.edu.au/cgi/users/home?screen=EPrint::View&eprintid=687">item control page</a></p>
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<!-- #EndLibraryItem -->
<div align="center"></div></td>
</tr>
</table>
</body>
</html>
