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Tag recommendation has gained significant popularity for annotating various web-based resources including web services. Compared with other approaches, tag recommendation based on supervised learning models usually lead to good accuracy. However, a high-quality training data set is needed, which demands manual tagging efforts from domain experts. While we could leverage the tags of existing web services...
The granularity partition for functional modules is a fundamental research topic in robot distributed control technology. How to evaluate the module partition scheme with different granularity, and then obtain the optimum scheme is the urgent problem. In this paper, we proposed a novel evaluation strategy for the granularity partition of functional modules in robotic system using RTM as control platform...
The task of community detection in a graph formalizes the intuitive task of grouping together subsets of vertices such that vertices within clusters are connected tighter than those in disparate clusters. This paper approaches community detection in graphs by constructing Markov random walks on the graphs. The mixing properties of the random walk are then used to identify communities. We use coupling...
In this paper, we present a cluster algorithm which is an improvement of the multi-objective clustering ensemble algorithm (MOCLE), which is denoted as IMOCLE for short. First, we introduce a new clustering objective function to measure the individual difference in the optimization process so as to remain the diversity of the population. Then, a clustering ensemble technique is applied to MOCLE to...
In a world of constant technological evolution, the expansion of location tracking technologies is a fact. Most of us may have a device which can tell us our location with more or less accuracy. Most of those devices collect our location information and, usually, the trajectories we make. Publishing this information is essential for companies to improve their marketing strategies, for the traffic...
Clustering is a common step in the analysis of microarray data. Microarrays enable simultaneous high-throughput measurement of the expression level of genes. These data can be used to explore relationships between genes and can guide development of drugs and further research. A typical first step in the analysis of these data is to use an agglomerative hierarchical clustering algorithm on the correlation...
In this paper we propose a similarity-based clustering algorithm for handling LR-type fuzzy numbers. The proposed method does not need to specify a cluster number and initial values in which it is robust to initial values, cluster number, cluster shapes, noise and outliers for clustering LR-type fuzzy data. Numerical examples and real data demonstrate the effectiveness of the proposed clustering algorithm.
The Web is overcrowded with news articles, an overwhelming information source both with its amount and diversity. Assigning news articles to similar groups, on the other hand, provides a very powerful data mining and manipulation technique for topic discovery from text documents. In this paper, we are investigating the application of a great spectrum of clustering algorithms, as well as similarity...
This paper describes an automatic text analysis of values contained in the Enron email dataset that seeks to explore the potential to apply value patterns to cluster a social network. Two hypotheses are posed: individuals communicate more frequently with other individuals who share similar value patterns than with individuals with different value patterns; and people who communicate more frequently...
Large, unwieldy classes are a significant maintenance problem. Programmers dislike them because the fundamental logic is often obscured, making them hard to understand and modify. This paper proposes a solution - a semi-automatic technique for splitting large classes into smaller, more cohesive ones. The core of the technique is the use of betweenness clustering to identify the best way of partitioning...
Due to the inherent correlation among Web objects and the lack of a uniform schema of Web documents, Web community mining and analysis has become an important area for Web data management and analysis. The research of Web communities spans a number of research domains such as Web mining, Web search, clustering and text retrieval. In this talk we will present some recent studies on this topic, which...
The paper deals with approaches to determination of the optimal number of groups of objects and finding outlying objects when objects are clustered by different methods implemented in commercial statistical software packages. These attempts are illustrated on example of finding groups of similar binary variables. The methods of cluster analysis, multidimensional scaling, factor analysis and Boolean...
A new method for image feature extraction and segmentation is proposed in this paper. Abundant contour feature information of the image is expressed by contourlet transform while texture feature of the image is described by wavelet transform and Gray Level Co-occurrence Matrix (GLCM). The three type feature information compose feature matrix. The presented method describes different image information...
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