The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when talk about patterns? We propose a practicable definition of concept pattern data distribution as combination multiple interrelated elements two or more components that can be represented treated unified whole. Our theoretical model describes how patterns are made by relationships...

Local pattern discovery, pattern set discovery and global modeling build together as consecutive steps a specific case of global pattern discovery. As each of these three steps have gained an increased attention in recent years, a great variety of techniques for each step have been proposed. Though so far there has been no systematic comparison of the possible choices. In this paper, we will co...

This paper formalizes a latent variable inference problem we call supervised pattern discovery, the goal of which is to find sets of observations that belong to a single “pattern.” We discuss two versions of the problem and prove uniform risk bounds for both. In the first version, collections of patterns can be generated in an arbitrary manner and the data consist of multiple labeled collection...

Today, the objective of public health surveillance system is to reduce the impact of outbreaks by enabling appropriate intervention. Commonly used techniques are based on the changes or aberration in health events when compared with normal history to detect an outbreak. The main problem encountered in outbreaks is high rates of false alarm. High false alarm rates can lead to unnecessary interve...

The number of crime committed based on the malware intrusion is never ending as the number of malware variants is growing tremendously and the usage of internet is expanding globally. Malicious codes easily obtained and use as one of weapon to gain their objective illegally. Hence, in this research, diverse logs from different OSI layer are explored to identify the traces left on the attacker a...

Statistically sound pattern discovery harnesses the rigour of statistical hypothesis testing to overcome many of the issues that have hampered standard data mining approaches to pattern discovery. Most importantly, application of appropriate statistical tests allows precise control over the risk of false discoveries — patterns that are found in the sample data but do not hold in the wider popul...

Driven Pattern Discovery In Databases Vasant Dhar and Alexander Tuzhilin Department of Information, Operations and Management Sciences Leonard N. Stem School of Business, New York University 44 West 4th Street, New York, NY 10012 vdhar@,stern.nvu.edu, atuzhilin@,stern.nvu.edu Center for Digltzl Economy Rrsaarch Stern School of Bushess W o r h g Paper IS-93-1 1 Abstract-Driven Pattern Discovery ...

Relevance feedback has been an indispensable component for multimedia retrieval systems. In this paper, we present an adaptive pattern discovery method, which addresses relevance feedback by interactively discovering meaningful patterns of relevant objects. To facilitate pattern discovery, we first present a dynamic feature extraction method, which aims to alleviate the curse of dimensionality ...