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Visual analytics plays a key role in bringing insights to audiences who are interested and dedicated in data exploration. In the area of relational data, many advanced visualization tools and frameworks are proposed in order to dealing with such data features. However, the majority of those have not greatly considered the whole process from data-model mining to query utilizing on dimensions and data...
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mining are exploration, confirmation and presentation of the clustering results. However, the most of visual techniques developed for cluster analysis are primarily focused on cluster presentation rather than cluster exploration. Several techniques have been proposed to explore cluster information by...
This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists,...
Big Data, structured and unstructured data, contains millions attributes in multiple dimensions. This has arisen threeissues: 1) how to measure the structured and unstructured multidimensional data patterns for Big Data analysis; 2) how to display multidimensional data patterns in normal size of screen; 3) how to optimize the data attributes in Big Data visualization. In this work, we have visual...
We present an image classification method which consists of salient region (SR) detection, local feature extraction, and pairwise local observations based Naive Bayes classifier (NBPLO). Different from previous image classification algorithms, we propose a scale, translation, and rotation invariant image classification algorithm. Based on the discriminative pairwise local observations, we develop...
Parallel coordinate is a popular tool for visualizing high-dimensional data and analyzing multivariate data. With the rapid growth of data size and complexity, data clutter in parallel coordinates is a major issue for Big Data visualization. This has given rise to three problems, 1) how to rearrange the parallel axes without the loss of data patterns, 2) how to shrink data attributes on each axis...
This paper extends a previous work on node link tree visualization and interaction by providing visual clues on hidden structures. We adopt the effectiveness of DOI Tree, a multi-focal tree layout algorithm, for exploring large hierarchical structures. The advantages of visualization are its most familiar mapping for users, its capability on providing multiple focused nodes, and its dynamic rescaling...
Visual cryptography is a way to encrypt the secret image into several meaningless share images. Noted that no information can be obtained if not all of the shares are collected. Stacking the share images, the secret image can be retrieved. The share images are meaningless to owner which results in difficult to manage. Tagged visual cryptography is a skill to print a pattern onto meaningless share...
Big Data, which contains image, video, text, audio and other forms of data, collected from multiple datasets, is difficult to process using traditional database management tools or applications. In this paper, we establish the 5Ws model by using 5Ws data dimension for Big Data analysis and visualization. 5Ws data dimension stands for, What the data content is, Why the data occurred, Where the data...
Flood attacks are common threats to Internet, which has necessitated the need for visual analysis within an intrusion detection system to identify these attacks patterns. The challenges are how to increase the accuracy of detection and how to visualize and present the patterns of flood attack for early detection. In this paper, we introduce a Two-Density model that contains two coefficients: sending-density...
Flood attack patterns have variability depending on the network environment. It has been necessitated that the need for visual analysis within an Intrusion Detection System (IDS) is to identify these flood-attack patterns. The challenges are how to increase the accuracy of detection and how to visualize and present flood attack patterns in networks for early detection. In this paper, we propose a...
Visual Sensitivity analysis has proven its feasibility in data exploration and exposing relationships between the variables in the model. However, it lacks the ability of user direct interaction of outputs. To overcome this drawback for this interdisciplinary field, in this paper we introduce a novel approach of integrating an interactive visualization and a sensitivity analysis method into a visual...
This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply RST to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear...
Visualization and interaction of multidimensional data always requires optimized solutions to integrate the display, exploration and analytical reasoning of data into one visual pipeline for human-centered data analysis and interpretation. Parallel coordinate, as one of the popular multidimensional data visualization techniques, is suffered from the visual clutter problem. Though changing the ordering...
Space-filling visualization techniques have proved their capability in visualizing large hierarchical structured data. However, most existing techniques restrict their partitioning process in vertical and horizontal direction only, which cause problem with identifying hierarchical structures. According to Gestalt research, limiting tree map visualisation to rectangles blocks the utilisation of human...
Biometric fusion is an essential procedure in any multi-modal biometric person recognition systems and it can be performed at sensor, feature, score and decision levels. This paper proposes a simulated annealing (SA) algorithm for the fusion of multi-modal biometric data. This method is applied to an Audio-Visual (AV) person recognition database that includes acoustic and visual information. Its superior...
Most learning-based video semantic analysis methods require a large training set to achieve good performances. However, annotating a large video is laborintensive. This paper introduces how to construct the training set and reduce user involvement. There are four selection schemes proposed: clustering-based, spatial dispersiveness, temporal dispersiveness, and sample-based which can be used construct...
Effective and efficient navigation and representation of the entire structure of the product catalog is one of the important factors for on-line market. This paper proposes an application using Treemaps visualization to enhance the functionality of online product category. We aim to develop high-quality catalog interfaces in terms of readability, understandability and comprehension by integrating...
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...
The traditional solutions to the stock market security are not sufficient in identifying attackers and further attack plans from the analysis of existing events.Therefore, it is difficult for analysts to prevent future unexpected events or frauds by only monitoring the realtime trading information. The event-driven fraud detection in financial market could not help analysts to find attack plans and...
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