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Industrial cluster, like the organism, has its own process of evolution. Clusters from birth to the growth stage, have completed the initial accumulation of capital, and began the evolution to the mature stage. How to successfully evolve becomes the research focus in the majority of scholars. In this paper, we study the dynamic factors of the growth stage of industrial clusters in HeBei Provice, JingXian...
With the boom of web and social networking, the amount of generated text data has increased enormously. Much of this data can be considered and modeled as a stream and the volume of such data necessitates the application of automated text classification strategies. Although streaming data classification is not new, considering text data streams for classification purposes has been extensively researched...
At present, most of the studies on the relationship between El Nino Southern Oscillation and agricultural futures focus on perceptual and directly data analysis. This article uses EMD algorithm on endpoints processed data to decompose wheat futures price into seven Intrinsic Mode Function and one Residue. Then do symbolic clustering combined with SSVS method and denoised ENSO index. The results not...
Many relationships naturally come in a bipartite setting: authors that write articles, proteins that interact with genes, or customers that buy, rent or rate products. Often we are interested in the clustering behavior of one side of the graph, i.e., in finding groups of similar articles or products. To find these clusters, a one-mode projection is classically applied, which results in a normal graph...
In this paper, factor analysis is applied on a set of data that was collected to study the effectiveness of 58 different agile practices. The analysis extracted 15 factors, each was associated with a list of practices. These factors with the associated practices can be used as a guide for agile process improvement. Correlations between the extracted factors were calculated, and the significant correlation...
This paper presents a method to improve the performance of Information Retrieval System (IRS) by increasing the no of relevant documents retrieved. There are several types of uncertainty and fuzziness associated with IRS like search term uncertainty, relevance uncertainty involved in retrieving of irrelevant documents. The aim of this paper is to eliminate different types of uncertainty and increase...
An attack activity to cyberspace will cause the security devices generating huge number of security events, it is unfeasible to analyze these events by the manual way for the security manager. After analyzing the existing algorithms of security events correlation, we propose an attack scenario reconstruction technology based on state machine. The processes of attackers intruding into the cyberspace...
In functional magnetic resonance imaging (fMRI) data, activated voxels are usually very small in number and are embedded in a mass of inactive voxels. For clustering analysis, this situation generates an ill-balanced data problem among different classes of voxels. In this paper we propose a novel method to overcome the ill-balanced data problem, by reducing the number of voxels to be processed by...
Most of the biclustering algorithms for the analysis of high dimensional gene expression data use some distance measure or correlation coefficient between a pair of genes as the similarity measure. These measures capture only linear relationships between the genes but non linear relationships may exist amongst them. Mutual information is a more general measure to investigate relationships (positive,...
Text clustering is an important task of text mining. The purpose of text clustering is grouping similar text documents together efficiently to meet human interests in information searching and understanding. The procedure of clustering should involve a cognitive process of text understanding or comprehension.This paper introduces an innovative research effort, CogHTC, a hierarchical text clustering...
Describes a method for learning classes of facial motion patterns from a video of a human interacting with a computerized embodied agent. The method also learns correlations between the discovered motion classes and the current interaction context. Our work is motivated by two hypotheses. First, a computer user's facial displays are context-dependent, especially in the presence of an embodied agent...
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