This paper proposed improved K-means clustering algorithm based on user tag. It first used social annotation data to expand the vector space model of K-means. Then, it applied the links involved in social tagging network to enhance the clustering performance. Experimental result shows that the proposed improved K-means clustering algorithm based on user tag is effective.

It is well-known that dimX ≤ n if and only if every map of a closed subspace of X into the n-dimensional sphere Sn can be extended over X. It is also well-known that for the cohomological dimension dimGX of X with respect to an abelian coefficient group G, dimGX ≤ n if and only if every map of a closed subspace of X into the Eilenberg-Mac Lane complex K(G,n) extends over X. These properties giv...

Human action recognition is an important yet challenging task. In this paper, a simple and efficient method based on random forests is proposed for human action recognition. First, we extract the 3D skeletal joint locations from depth images. The APJ3D computed from the action depth image sequences by employing the 3D joint position features and the 3D joint angle features, and then clustered i...

In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present th...

A new algorithm is proposed which accelerates the mini-batch k-means algorithm of Sculley (2010) by using the distance bounding approach of Elkan (2003). We argue that, when incorporating distance bounds into a mini-batch algorithm, already used data should preferentially be reused. To this end we propose using nested mini-batches, whereby data in a mini-batch at iteration t is automatically re...

A modified method for better superpixel generation based on simple linear iterative clustering (SLIC) is presented and named BSLIC in this paper. By initializing cluster centers in hexagon distribution and performing k-means clustering in a limited region, the generated superpixels are shaped into regular and compact hexagons. The additional cluster centers are initialized as edge pixels to imp...

This paper attempts to discover the most desired attributes of a model ERP implementation project. The analysis, based on research conducted among a few dozen companies implementing an ERP system, employs the statistical methods of element grouping. First, using an agglomeration method, the number of groups was determined, which was used as a parameter in the subsequently applied k-Means method...

There is often a large disparity between the size of a game we wish to solve and the size of the largest instances solvable by the best algorithms; for example, a popular variant of poker has about 10 nodes in its game tree, while the currently best approximate equilibrium-finding algorithms scale to games with around 10 nodes. In order to approximate equilibrium strategies in these games, the ...