In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is pos...
Association rule mining techniques are used to search attribute-value pairs that occur frequently together in a data set. Ordinal association rules are a particular type of associa...
Alina Campan, Gabriela Serban, Traian Marius Truta...
- Research work related to applying text categorization methods to a monolingual corpus such as English text collections has been well established by several research teams in rece...
Abstract-- In this paper we consider d-dimensional spatiotemporal data (d 1) and ways to approximate and index it. We focus on indexing such data for similarity matching using orth...
In large telecommunication networks, alarms are usually useful for identifying faults and, therefore solving them. However, for large systems the number of alarms produced is so la...
Common document clustering algorithms utilize models that either divide a corpus into smaller clusters or gather individual documents into clusters. Hierarchical Agglomerative Clus...
Process monitoring refers to the task of detecting abnormal process operations resulting from the shift in the mean and/or the variance of one or more process variables. To success...
—In this paper we present graph-based approaches to mining for anomalies in domains where the anomalies consist of unexpected entity/relationship alterations that closely resembl...
— The application of feature selection techniques greatly reduces the computational cost of classifying highdimensional data. Feature selection algorithms of varying performance ...
Lauren Burrell, Otis Smart, George J. Georgoulas, ...