We propose a new technique for clustering of text documents that relies on a biclustering structure constructed on terms and documents. Our approach makes use of a greedy algorith...
Many existing techniques for term extraction are heuristically-motivated and criticised as ad-hoc. The definitions and assumptions critical to set the boundary for the effective...
In this paper, we propose a semi-supervised framework for learning a weighted Euclidean subspace, where the best clustering can be achieved. Our approach capitalizes on user-const...
Maria Halkidi, Dimitrios Gunopulos, Nitin Kumar, M...
This paper presents an application of PageRank for assigning documents with a corresponding geographical scope. We describe the technique in detail, together with its theoretical ...
In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments sho...