Cbtv: Visualising Case Bases For Similarity Measure Design And Selection,
2010
Technological University Dublin
Cbtv: Visualising Case Bases For Similarity Measure Design And Selection, Brian Mac Namee, Sarah Jane Delany
Conference papers
In CBR the design and selection of similarity measures is paramount. Selection can benefit from the use of exploratory visualisation- based techniques in parallel with techniques such as cross-validation ac- curacy comparison. In this paper we present the Case Base Topology Viewer (CBTV) which allows the application of different similarity mea- sures to a case base to be visualised so that system designers can explore the case base and the associated decision boundary space. We show, using a range of datasets and similarity measure types, how the idiosyncrasies of particular similarity measures can be illustrated and compared in CBTV allowing …
Trust-Oriented Composite Service Selection With Qos Constraints,
2010
Singapore Management University
Trust-Oriented Composite Service Selection With Qos Constraints, Lei Li, Yang Wang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In Service-Oriented Computing (SOC) environments, service clients interact with service providers for consuming services. From the viewpoint of service clients, the trust level of a service or a service provider is a critical factor to consider in service selection, particularlywhen a client is looking for a service from a large set of services or service providers. However, a invoked service may be composed of other services. The complex invocations in composite services greatly increase the complexity of trust-oriented service selection. In this paper, we propose novel approaches for composite service representation, trust evaluation and trust-oriented com-posite service selection (with QoS …
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.
An Optical Machine Vision System For Applications In Cytopathology,
2010
Technological University Dublin
An Optical Machine Vision System For Applications In Cytopathology, Jonathan Blackledge, Dmitry Dubovitskiy
Articles
This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image focusing on problem in Cytopathology. A unique self learning procedure is presented in order to incorporate expert knowledge. The classification method is based on the application of a set of features which includes fractal parameters such as the Lacunarity and Fourier dimension. Thus, the approach includes the characterisation of an object in terms of its fractal properties and texture characteristics. The principal issues associated with object recognition are presented which include the basic model and segmentation algorithms. The self-learning procedure for …
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 …
Anonymous Query Processing In Road Networks,
2010
Singapore Management University
Anonymous Query Processing In Road Networks, Kyriakos Mouratidis, Man Lung Yiu
Research Collection School Of Computing and Information Systems
The increasing availability of location-aware mobile devices has given rise to a flurry of location-based services (LBSs). Due to the nature of spatial queries, an LBS needs the user position in order to process her requests. On the other hand, revealing exact user locations to a (potentially untrusted) LBS may pinpoint their identities and breach their privacy. To address this issue, spatial anonymity techniques obfuscate user locations, forwarding to the LBS a sufficiently large region instead. Existing methods explicitly target processing in the euclidean space and do not apply when proximity to the users is defined according to network distance …
