Robust Report Level Cluster-to-Track Fusion

In this paper we develop a method for report level tracking based on Dempster-Shafer clustering using Potts spin neural networks where clusters of incoming reports are gradually fused into existing tracks, one cluster for each track. Incoming reports are put into a cluster and continuous reclustering of older reports is made in order to obtain maximum association fit within the cluster and towards the track. Over time, the oldest reports of the cluster leave the cluster for the fixed track at the same rate as new incoming reports are put into it. Fusing reports to existing tracks in this fashion allows us to take account of both existing tracks and the probable future of each track, as represented by younger reports within the corresponding cluster. This gives us a robust report-to-track association. Compared to clustering of all available reports this approach is computationally faster and has a better report-to-track association than simple step-by-step association.Comment: 6 pages, 5 figure

Median evidential c-means algorithm and its application to community detection

Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed. The median variant relaxes the restriction of a metric space embedding for the objects but constrains the prototypes to be in the original data set. Due to these properties, MECM could be applied to graph clustering problems. A community detection scheme for social networks based on MECM is investigated and the obtained credal partitions of graphs, which are more refined than crisp and fuzzy ones, enable us to have a better understanding of the graph structures. An initial prototype-selection scheme based on evidential semi-centrality is presented to avoid local premature convergence and an evidential modularity function is defined to choose the optimal number of communities. Finally, experiments in synthetic and real data sets illustrate the performance of MECM and show its difference to other methods

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

Evaluating computational creativity: a standardised procedure for evaluating creative systems and its application

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system’s creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system’s strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems’ creativity, informing further progress in computational creativity research

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation