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Finding of frequent sub-graphs is an important operation on graphs and it is defined as detection of all sub-graphs that appear frequently in a set of graphs. This paper proposes detection of frequent sub-community graph from n-set of community graph of villages; are useful for characterizing community graph sets, finding difference among groups of community graphs, classifying and clustering of community...
Based on a distance of kernel method, a novel noise-resistant fuzzy clustering algorithm called kernel noise clustering (KNC) algorithm, is proposed. KNC is an extension of the noise clustering (NC) algorithm proposed by Dave. By replacing the Euclidean distance used in the objective function of NC algorithm, a new distance is introduced in NC algorithm. The distance of the kernel method is more robust...
A major use of microarray data is to classify genes with similar expression profiles into groups in order to investigate their biological significance. Cluster analysis is by far the most used technique for gene expression analysis. It has grown to be an important research topic in a wide variety of fields owing to its wide applications. A number of clustering methods exist with one or more limitations,...
In the problem of face clustering with multi-views, the similarity between faces of different persons with similar pose is usually greater than the similarity between multi-view faces of the same person. This may exert a tremendous impact on the clustering result that sent back to the user. To solve this problem, we should do pose clustering first and then within each dasiapose grouppsila, clustering...
Due to user??s inability to define his service requirement in a precise way, the services returned by service search engine (SSE) are mostly inadequate or inaccurate. Taking a clustering method on its potential search results would not only improve its search utility , but also enhance its effectiveness and accuracy than traditional ranked-list style in helping users to find relevant services . For...
The application of wireless sensor network (WSN) is always restricted by the energy shortage of sensor nodes. In order to reduce the entire energy consumption of the WSN, a promising approach is to design light clustering algorithms. LEACH is such a well-known clustering algorithm that was designed to distribute the energy consumption to nodes in the WSN evenly. LEACH is characterized by its attractive...
The rapid development of multimedia applications over the past decade requires efficient methods for video browsing. In this paper, we present an algorithm for video summarization with shot comparison. We analyze video content in the shot level, and we calculate the shot distance using the advanced Hausdorff distance. The advanced Hausdorff distance combines the Hausdorff distance and Boolean model,...
Video summarization is a useful tool which allows a user to grasp rapidly the essence of a video. In the development of this research topic we propose a new method based on different individual content segmentation and selection tools in a collaborative system. The main innovation of this work is to merge results from different approaches, so as to benefit from their respective qualities. Our system...
The methods to select supply chain partners for a corporation is very important, especially for the complicated supply chain network with hundreds of members and multilevel structure , and the increasingly developing of evaluation criteria. According to the situation, we propose RVPK algorithm based on PSO (particle swarm optimization) and k-means clustering. The method is applied on clustering of...
In recent past, there is an increased interest in time series clustering research, particularly for finding useful similar trends in multivariate time series in various applied areas such as environmental research, finance, and crime. Clustering multivariate time series has potential for analyzing large volume of crime data at different time points as law enforcement agencies are interested in finding...
In a knowledge driven economy information plays an important role. Different entities of society are seeking varied information on a day to day basis. In every walk of life decision makers are taking decisions after careful analysis of relevant information. Hence quality of decisions eventually depends upon quality of information. With the advent of Internet technology the population of online information...
This paper studies the problem of weighting and selecting attributes and principal axes in fuzzy clustering. Its main contribution is a selection method that is not based on simply applying a threshold to computed feature weights, but directly assigns zero weights to features that are not informative enough. This has the important advantage that the clustering result that can be obtained on the selected...
Bug tracking systems are important tools that guide the maintenance activities of software developers. The utility of these systems is hampered by an excessive number of duplicate bug reports-in some projects as many as a quarter of all reports are duplicates. Developers must manually identify duplicate bug reports, but this identification process is time-consuming and exacerbates the already high...
A natural Euclidean space is defined on a set of texts as sequences or hierarchical structures. Unlike the traditional term-document model, the present model takes local topological structure of texts. Kernel functions are defined that enable the use of Euclidean spaces and hence methods of data analysis based on kernels are applicable to the present model. Applications include agglomerative as well...
Person retrieval and indexing in video sequences is a challenging task for many multimedia applications. This paper proposes a new method that index the person based on the similarity. Firstly, the persons in a shot are detected and tracked through face detector and continuously adaptive mean shift algorithm. Then mid-level features such as clothes colors and voice are applied to represent the person...
We describe an approach to identifying specific settings in large collections of photographs corresponding to a visual diary. An algorithm developed for setting detection should be capable of clustering images captured at the same real world locations (e.g. in the dining room at home, in front of the computer in the office, in the park, etc.). This requires the selection and implementation of suitable...
A novel concept called wireless ad-hoc control networks (WACNets), exploring an ad-hoc approach to networked distributed control, has been under study for the last five years in the research group. Such systems represent a new stage in the evolution of distributed control and monitoring. The work carried out in developing an adaptive self-organisation algorithm for WACNet is reported. The algorithm...
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