Modeling Anticipatory Event Transitions,
2010
Nanyang Technological University
Modeling Anticipatory Event Transitions, He Qi, Kuiyu Chang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Major world events such as terrorist attacks, natural disasters, wars, etc. typically progress through various representative stages/states in time. For example, a volcano eruption could lead to earthquakes, tsunamis, aftershocks, evacuation, rescue efforts, international relief support, rebuilding, and resettlement, etc. By analyzing various types of catastrophical and historical events, we can derive corresponding event transition models to embed useful information at each state. The knowledge embedded in these models can be extremely valuable. For instance, a transition model of the 1918-1920 flu pandemic could be used for the planning and allocation of resources to decisively respond to future occurrences of …
Dual Phase Learning For Large Scale Video Gait Recognition,
2010
Singapore Management University
Dual Phase Learning For Large Scale Video Gait Recognition, Jialie Shen, Hwee Hwa Pang, Dacheng Tao, Xuelong Li
Research Collection School Of Computing and Information Systems
Accurate gait recognition from video is a complex process involving heterogenous features, and is still being developed actively. This article introduces a novel framework, called GC2F, for effective and efficient gait recognition and classification. Adopting a ”refinement-and-classification” principle, the framework comprises two components: 1) a classifier to generate advanced probabilistic features from low level gait parameters; and 2) a hidden classifier layer (based on multilayer perceptron neural network) to model the statistical properties of different subject classes. To validate our framework, we have conducted comprehensive experiments with a large test collection, and observed significant improvements in identification accuracy relative to …
Information Integration For Graph Databases,
2010
Singapore Management University
Information Integration For Graph Databases, Ee Peng Lim, Aixin Sun, Anwitaman Datta, Chang Kuiyu
Research Collection School Of Computing and Information Systems
With increasing interest in querying and analyzing graph data from multiple sources, algorithms and tools to integrate different graphs become very important. Integration of graphs can take place at the schema and instance levels. While links among graph nodes pose additional challenges to graph information integration, they can also serve as useful features for matching nodes representing real-world entities. This chapter introduces a general framework to perform graph information integration. It then gives an overview of the state-of-the-art research and tools in graph information integration.
