Keith Chan

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Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging(More)
The software processes can be analyzed, designed, and maintained as if it is a piece of software. This view enables the application of software engineering technologies to software process modeling (SPM) and process-centered software engineering environment (PSEE). One reason for the relatively few applications of SPMs and PSEEs technologies in the software(More)
Nowadays, the majority of productivity applications are interactive and graphical in nature. In this paper, we explore the possibility of taking advantage of these two characteristics in a design recovery tool. Specifically, the fact that an application is interactive means that we can identify distinct execution bursts corresponding closely to "actions"(More)
This paper presents two genetic algorithm (GA) based hybrid approaches for the prediction of tumor outcomes based on gene expression data. One approach is the hybrid GA and K-medoids for grouping genes based on the commonly used distance similarity. The goal of grouping genes here is to choose some top-ranked representatives from each cluster for gene(More)
Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. This paper summarizes the(More)
Nowadays, the majority of productivity applications are interactive and graphical in nature. In this demonstration, we explore the possibility of taking advantage of these two characteristics in a design recovery tool. Specifically, the fact that an application is interactive means that we can identify distinct execution bursts corresponding closely to(More)
An attributed graph contains vertices that are associated with a set of attribute values. Mining clusters or communities, which are interesting subgraphs in the attributed graph is one of the most important tasks of graph analytics. Many problems can be defined as the mining of interesting subgraphs in attributed graphs. Algorithms that discover subgraphs(More)
This paper presents a graph clustering algorithm, called EGCPI, to discover protein complexes in protein-protein interaction (PPI) networks. In performing its task, EGCPI takes into consideration both network topologies and attributes of interacting proteins, both of which have been shown to be important for protein complex discovery. EGCPI formulates the(More)
We are living in a world where information is critical for better daily decision making. Information is available everywhere. The paramount issue concerning information is therefore not about availability but about findability, and that information has to be made available in the right context. Information is available in abundance and if we can turn(More)