We propose a hybrid, unsupervised document clustering approach that combines a hierarchical clustering algorithm with Expectation Maximization. We developed several heuristics to ...
Background: Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function). Standar...
Timothy J. Harlow, J. Peter Gogarten, Mark A. Raga...
This paper presents a general framework for agglomerative hierarchical clustering based on graphs. Specifying an inter-cluster similarity measure, a subgraph of the similarity gra...
act Weighting Framework for Clustering Algorithms Richard Nock Frank Nielsen Recent works in unsupervised learning have emphasized the need to understand a new trend in algorithmi...
The efficient subdivision of a sensor network into uniform, mostly non-overlapping clusters of physically close nodes is an important building block in the design of efficient uppe...