This paper presents an approximation of word clustering, using only function words as context. We use this to induce classes of function words. Our algorithm identifies some classes with consistency, and could be useful for guiding greedy grammar learners.

Clustering algorithms play an important role in data analysis and information retrieval. How to obtain a clustering for a large set of highdimensional data suitable for database applications remains a challenge. We devise in this paper a set-theoretic clustering method called PCS (Pairwise Consensus Scheme) for high-dimensional data. Given a large set of d-dimensional data, PCS first constructs...

We introduce a novel algorithm for hierarchical clustering on planar graphs we call “Hierarchical Greedy Planar Correlation Clustering” (HGPCC). We formulate hierarchical image segmentation as an ultrametric rounding problem on a superpixel graph where there are edges between superpixels that are adjacent in the image. We apply coordinate descent optimization where updates are based on planar c...

Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high modularity in a small amount of time. In an effort to use the power offered by multi-core CPU and GPU hardware to solve the clustering problem, we introduce a fine-grained shared-memory parallel graph coarsening algorithm and use this to implement a parallel agglomerative clustering heuristic on bo...

in recent years stock exchange has become one of the most attractive and growing businesses in respect of investment and profitability. but applying a scientific approach in this field is really troublesome because of variety and complexity of decision making factors in the field. this paper tries to deliver a new solution for portfolio selection based on multi criteria decision making literatu...

For the linear least squares problem with coefficient matrix columns being highly correlated, we develop a greedy randomized Gauss-Seidel method oblique direction. Then corresponding convergence result is deduced. Numerical examples demonstrate that our proposed superior to and

ontology is the main infrastructure of the semantic web which provides facilities for integration, searching and sharing of information on the web. development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ontology matching. by emerging large-scale ontologies in real domain, the ontology matching systems faced with some problem like memory con...

Location-Routing Problem (LRP) is related to logistics system of supply chain. In LRP, aims are facility location problem and vehicle routing problem that are considered simultaneously. As shown in recent researches, the costs in distribution systems may be excessive if routes are ignored when locating depots. In this paper, a heuristic method in four phases is developed to solve Capacitated Lo...

We propose a method for learning the intrinsic topology of a point set sampled from a curve embedded in a high-dimensional ambient space. Our approach does not rely on distances in the ambient space, and thus can recover the topology of sparsely sampled curves, a situation where extant manifold learning methods are expected to fail. We formulate a loss function based on the smoothness of a curv...