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An approach to identification of the phishing target of a given (suspicious) webpage is proposed by clustering the webpage set consisting of its all associated webpages and the given webpage itself. We first find its associated webpages, and then explore their relationships to the given webpage as their features for clustering. Such relationships include link relationship, ranking relationship, text...
Bipartite graphs are often used to illustrate relationships between two sets of data, such as web pages and visitors. At the same time, information is often organized hierarchically, for example, web pages are divided into directories by their contents. The hierarchical structures are useful for analyzing information. Graphs with both a bipartite structure and a hierarchical structure are called “clustered...
Object category recognition is a challenging task due to the low level and non-discrimination in visual representation. Most previous methods concentrate to find better high level visual features. Recently, optimally integrating various features to solve the problem attracted more interests. In this paper, we provide a novel method for object category recognition by improving the popular bag-of-words...
Many different approaches have been proposed for the challenging problem of visually analyzing large networks. Clustering is one of the most promising. In this paper we propose a new goal for clustering that is especially tailored to hybrid-visualization tools. Namely, that of producing both intra-cluster graphs and inter-cluster graph that are suitable for highly-readable visualizations within different...
The blogshpere is a huge community which contains lots of groups which are formed based on different purpose, such as interest based, working based and company based. People always urge to find these kinds of groups to gain related information. Having this idea, we propose a clustering based visualization interface using keywords graph to contribute special techniques for exploring those groups and...
In this paper, we present a system for the interactive visualization and exploration of graphs with many weakly connected components. The visualization of large graphs has recently received much research attention. However, specific systems for visual analysis of graph data sets consisting of many components are rare. In our approach, we rely on graph clustering using an extensive set of topology...
Visualization has become integral to the knowledge discovery process across various domains. However, challenges remain in the effective use of visualization techniques, especially when displaying, exploring and analyzing large, multidimensional datasets, such as weather and meteorological data. Direct visualizations of such datasets tend to produce images that are cluttered with excess detail and...
Lasso selection tends to be inefficient in many circumstances such as selecting spatially large clusters. ICE-Lasso is a novel technique that infers likely target clusters during an ongoing lasso gesture. It provides efficient gesture-based interaction techniques as shortcuts to select partial, complete, and multiple clusters. Additionally, it is overloaded on the traditional lasso via automatic mode...
This paper proposes a new interactive visualization for analyzing large hierarchical structures and networks. The technique combines of different graph layout methods with a layout refinement process, an interactive navigation mechanism and clustering algorithms. The integration of these components makes it flexible in dealing with a variety of graph and hierarchical structures. Interactive exploration...
Clustering techniques are heuristic processes that typically do not yield one optimal solution. Therefore it is common practice to generate multiple cluster sets and investigate the consistency of the record groupings. Fuzzy clustering essentially achieves the same objective by providing a measure of the extent to which each record belongs to each cluster i.e. the strength of association of each record...
In this paper, we present a user study on a novel video search interface based on the concept of aspect browsing. We aim to confirm whether automatically suggesting new aspects can increase the performance of an aspect-based browser. The proposed strategy is to assist the user in exploratory video search by actively suggesting new query terms and video shots. We use a clustering technique to identify...
Visual-interactive cluster analysis provides valuable tools for effectively analyzing large and complex data sets. Due to desirable properties and an inherent predisposition for visualization, the Kohonen Feature Map (or self-organizing map, or SOM) algorithm is among the most popular and widely used visual clustering techniques. However, the unsupervised nature of the algorithm may be disadvantageous...
Radviz is a radial visualization with dimensions assigned to points called dimensional anchors (DAs) placed on the circumference of a circle. Records are assigned locations within the circle as a function of its relative attraction to each of the DAs. The DAs can be moved either interactively or algorithmically to reveal different meaningful patterns in the dataset. In this paper we describe Vectorized...
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