Mining frequent subgraphs is an area of research where we have a given set of graphs, and where we search for (connected) subgraphs contained in many of these graphs. Each graph can be seen as a transaction, or as a molecule — as the techniques applied in this paper are used in (bio)chemical analysis. In this work we will discuss an application that enables the user to further explore the resul...

The pattern recognition problem in Ring Imaging CHerenkov (RICH) counters concerns the identification of an unknown number of rings whose centers and radii are assumed to be unknown. In this paper we present an algorithm based on the possibilistic approach to clustering that automatically finds both the number of rings and their position without any a priori knowledge. The algorithm has been te...

This paper presents a novel approach for video-based face recognition. We define a metric based on an average 2 L Euclidean distance between two videos as the classifier. This metric makes use of Earth Mover’s Distance (EMD) as the underlying similarity measurement between videos. Earth Mover’s Distance is a recently proposed metric for geometric pattern matching and it reflects the average gro...

Automatic recognition of abnormal patterns in control charts has seen increasing demands nowadays in manufacturing processes. This paper presents a novel hybrid intelligent method (HIM) for recognition of the common types of control chart pattern (CCP). The proposed method includes two main modules: a clustering module and a classifier module. In the clustering module, the input data is first c...

Controlling false acceptance errors is of critical importance in many pattern recognition applications, including signature and speaker veri$cation problems. Toward this goal, this paper presents two post-processing methods to improve the performance of hyperspherical classi$ers in rejecting patterns from unknown classes. The $rst method uses a self-organizational approach to design minimum rad...

This chapter analyzes the problem of data cleansing and the identification of potential errors in data sets. The differing views of data cleansing are surveyed and reviewed and a brief overview of existing data cleansing tools is given. A general framework of the data cleansing process is presented as well as a set of general methods that can be used to address the problem. The applicable metho...

Though most approaches to protein comparison are based on their structure, several studies produced evidence of a strict correlation between the surface characteristics of proteins and the way they interact. Surface-based techniques for protein comparison typically require applying clustering algorithms to the punctual 3D description of the surface in order to produce a compact surface represen...

OBJECTIVE To report cluster breathing pattern associated with a nonbrainstem lesion. DESIGN Case report. SETTING Neurointensive care unit, St Mary's Hospital, Rochester, Minn. PATIENT A patient with subarachnoid hemorrhage developed severe, diffuse, distal bilateral middle cerebral artery vasospasm with resultant cortical laminar necrosis and transient cluster breathing. Intervention Magn...

This paper argues about pitch pattern variations of user utterances in human-machine dialogue. For intelligent humanmachine communication, it is essential that machines understand prosodic characteristics which imply a user's various attitude, emotion and intention beyond vocabulary. Our original focus is on particularly distinct pitch patterns and their roles in the actual dialogues. We used h...

Agglomerative clustering generates the partition hierarchically by a sequence of merge operations. We propose an alternative to the merge-based approach by removing the clusters iteratively one by one until the desired number of clusters is reached. We apply local optimization strategy by always removing the cluster that increases the distortion the least. Data structures and their update strat...