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 ...

The prominence of weakly labeled data gives rise to a growing demand for object detection methods that can cope with minimal supervision. We propose an approach that automatically identifies discriminative configurations of visual patterns that are characteristic of a given object class. We formulate the problem as a constrained submodular optimization problem and demonstrate the benefits of th...

The landscape of online learning has evolved in a synchronous fashion with the development of the every-growing repertoire of technologies, especially with the recent addition of Massive Online Open Courses (MOOCs). Since MOOC platforms allow thousands of students to participate at the same time, MOOC participants can have fairly varied motivation. Meanwhile, a low course completion rate has be...

Business processes have tremendously changed the way large companies conduct their business: The integration of information systems into the workflows of their employees ensures a high service level and thus high customer satisfaction. One core aspect of business process engineering are events that steer the workflows and trigger internal processes. Strict requirements on interval-scaled tempor...

We discuss the frequent pattern mining problem in a general setting. From an analysis of abstract representations, summarization and frequent pattern mining, we arrive at a generalization of the problem. Then, we show how the problem can be cast into the powerful language of algorithmic information theory. This allows us to formulate a simple algorithm to mine for all frequent patterns. 1

Pattern mining from the web log data leads to discovery of usage patterns of the user who navigate the web. Patterns which appear frequently in the web log data are item-sets and sequences. In this paper, a novel algorithm Intelligent Generalized Sequential pattern (IGSP) is designed which shows better results than the Generalized Sequential Pattern (GSP) algorithm. Experiment is conducted with...