Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
Traditional clustering focuses on finding a single best clustering solution from data. However, given a single data set, one could interpret it in different ways. This is particul...
Visualising large graphs faces the challenges of both data complexity and visual complexity. This paper presents a framework for visualising large graphs that reduces data complex...
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Authorship identification can be seen as a single-label multi-class text categorization problem. Very often, there are extremely few training texts at least for some of the candida...