"Short-text clustering" is a very important research field due to the current tendency for people to use very short documents, e.g. blogs, text-messaging and others. In s...
In this paper, we propose an efficient and effective method to find arbitrarily oriented subspace clusters by mapping the data space to a parameter space defining the set of possi...
In data clustering, many approaches have been proposed such as K-means method and hierarchical method. One of the problems is that the results depend heavily on initial values and...
The identification of categories in image databases usually relies on clustering algorithms that only exploit the feature-based similarities between images. The addition of semant...
We propose a scalable technique called Seeded Clustering that allows us to maintain R-tree indices by bulk insertion while keeping pace with high data arrival rates. Our approach ...