检索结果-内蒙古大学图书馆

IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Enrico Bertini Juri Buchmüller Fabian Fischer Stephan Huber Thomas Lindemeier Fabian Maaß Florian Mansmann Thomas Ramm Michael Regenscheit Christian Rohrdantz Christian Scheible Tobias Schreck Stephan Sellien Florian Stoffel Mark Tautzenberger Matthias Zieker Daniel A. Keim Data Analysis and Visualization Group University of Konstanz Germany

The task of the VAST 2011 Grand Challenge was to investigate potential terrorist activities and their relation to the spread of an epidemic. Three different data sets were provided as part of three Mini Challenges (MCs). MC 1 was about analyzing geo-tagged microblogging (Twitter) messages to characterize the spread of an epidemic. MC 2 required analyzing threats to a computer network using a situational awareness approach. In MC 3 possible criminal and terrorist activities were to be analyzed based on a collection of news articles. To solve the Grand Challenge, insight from each of the individual MCs had to be integrated appropriately.

关键词： Tag clouds Software Visual analytics data analysis Terrorism Rivers Imaging

来源：评论

学校读者我要写书评

暂无评论

SolarMap: Multifaceted Visual Analytics for Topic Exploration

SolarMap: Multifaceted Visual Analytics for Topic Exploratio...

引用

IEEE International conference on data Mining (ICDM)

作者： Nan Cao David Gotz Jimeng Sun Yu-Ru Lin Huamin Qu Hong Kong University of Science and Technology Hong Kong China IBM Thomas J. Watson Research Center USA Harvard University Northeastern University USA

Documents in rich text corpora often contain multiple facets of information. For example, an article from a medical document collection might consist of multifaceted information about symptoms, treatments, causes, diagnoses, prognoses, and preventions. Thus, documents in the collection may have different relations across each of these various facets. Topic analysis and exploration for such multi-relational corpora is a challenging visual analytic task. This paper presents Solar Map, a multifaceted visual analytic technique for visually exploring topics in multi-relational data. Solar Map simultaneously visualizes the topic distribution of the underlying entities from one facet together with keyword distributions that convey the semantic definition of each cluster along a secondary facet. Solar Map combines several visual techniques including 1) topic contour clusters and interactive multifaceted keyword topic rings, 2) a global layout optimization algorithm that aligns each topic cluster with its corresponding keywords, and 3) 2) an optimal temporal network segmentation and layout method that renders temporal evolution of clusters. Finally, the paper concludes with two case studies and quantitative user evaluation which show the power of the Solar Map technique.

关键词： Layout data visualization visualization Tag clouds data models Kernel Diseases

来源：评论

学校读者我要写书评

暂无评论

Reveling the Evolution of Semantic Content through Visual analysis

Reveling the Evolution of Semantic Content through Visual An...

引用

International conference on Advanced Learning Technologies (ICALT)

作者： D.A. Gomez-Aguilar M.A. Conde-Gonz´lez R. Theron F.J. Garcia-Penalvo Computer Science Department University of Sakamanca Spain Computer Science Department Computer Science Department /Science Education Research Institute /GRIAL Research Group University of Salamanca Spain

The literature in educational research has established that monitoring student learning is a crucial component of high quality education. When instructors and students are not in a face-to-face traditional environment, new forms of student monitoring must be explored. The effective use of CMS requires that instructors been provided with appropriate means of diagnosing problems so that they can take immediate actions to prevent or overcome those situations. The aim of this research is to support the comprehension of the evolution of the semantic content within eLearning environments through uncovering by means of visual representations. Therefore, we have carried out the mining of an eLearning database and represented the more relevant results by depicting them using a visualization based in the tag cloud visual representation. In this paper, we introduce a visual representation, which integrate a wave-graph and a bar-graph into a tag cloud representation to understand the evolution of words.

关键词： Tag clouds visualization Semantics data visualization Electronic learning Cloud computing Layout

来源：评论

学校读者我要写书评

暂无评论

Reputation-aware Filtering Services for Citizen Science data

Reputation-aware Filtering Services for Citizen Science Data

引用

IEEE International conference on E-Science Workshops

作者： Charles Brooking Jane Hunter School ITEE University of Queensland Brisbane Australia

The Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in "citizen science" projects by contributing data to scientific programs. However, the limited expertise of contributors can lead to poor quality or misleading data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research. In this paper, we describe how online reputation models can be adapted for citizen science projects to provide a simple and effective mechanism for assessing the reliability of community-generated data. We also describe the reputation aware querying, filtering and visualization services that we have developed that enable users to distinguish between datasets based on the reputation of the source/contributor. The resulting services are evaluated in the context of the Coral Watch project which uses volunteers to collect data on coral reef bleaching.

关键词： data models Bleaching Image color analysis Communities Reliability Monitoring Educational institutions

来源：评论

学校读者我要写书评

暂无评论

Accelerated learning of Generalized Sammon Mappings

Accelerated learning of Generalized Sammon Mappings

引用

International Joint conference on Neural Networks (IJCNN)

作者： Yinjie Huang Michael Georgiopoulos Georgios C. Anagnostopoulos Department of EE & CS University of Central Florida Orlando FL USA Electrical & Computer Engineering Department Florida Institute of Technology Melbourne FL USA

The Sammon Mapping (SM) has established itself as a valuable tool in dimensionality reduction, manifold learning, exploratory data analysis and, particularly, in data visualization. The SM is capable of projecting high-dimensional data into a low-dimensional space, so that they can be visualized and interpreted. This is accomplished by representing inter-sample dissimilarities in the original space by Euclidean inter-sample distances in the projection space. Recently, Kernel Sammon Mapping (KSM) has been shown to subsume the SM and a few other related extensions to SM. Both of the aforementioned models feature a set of linear weights that are estimated via Iterative Majorization (IM). While IM is significantly faster than other standard gradient-based methods, tackling data sets of larger than moderate sizes becomes a challenging learning task, as IM's convergence significantly slows down with increasing data set cardinality. In this paper we derive two improved training algorithms based on Successive Over-Relaxation (SOR) and Parallel Tangents (PARTAN) acceleration, that, while still being first-order methods, exhibit faster convergence than IM. Both algorithms are relatively easy to understand, straightforward to implement and, performance-wise, are as robust as IM. We also present comparative results that illustrate their computational advantages on a set of benchmark problems.

关键词： Acceleration Stress Kernel data visualization Convergence Training Prototypes

来源：评论

学校读者我要写书评

暂无评论

Visual sentiment analysis on twitter data streams

Visual sentiment analysis on twitter data streams

引用

IEEE Symposium on Visual Analytics Science and Technology (VAST)

作者： Ming Hao Christian Rohrdantz Halldór Janetzko Umeshwar Dayal Daniel A. Keim Lars-Erik Haug Mei-Chun Hsu Hewlett Packard Laboratory USA Hewlett-Packard Laboratories University of Konstanz Germany

Twitter currently receives about 190 million tweets (small text-based Web posts) a day, in which people share their comments regarding a wide range of topics. A large number of tweets include opinions about products and services. However, with Twitter being a relatively new phenomenon, these tweets are underutilized as a source for evaluating customer sentiment. To explore high-volume twitter data, we introduce three novel time-based visual sentiment analysis techniques: (1) topic-based sentiment analysis that extracts, maps, and measures customer opinions; (2) stream analysis that identifies interesting tweets based on their density, negativity, and influence characteristics; and (3) pixel cell-based sentiment calendars and high density geo maps that visualize large volumes of data in a single view. We applied these techniques to a variety of twitter data, (e.g., movies, amusement parks, and hotels) to show their distribution and patterns, and to identify influential opinions.

关键词： Twitter data visualization Calendars Motion pictures data mining Visual analytics

来源：评论

学校读者我要写书评

暂无评论

The auto-adjustment of electronic map color based on the provincial area mode of China

The auto-adjustment of electronic map color based on the pro...

引用

International conference on Geoinformatics

作者： Yao Zhou Jing'ai Wang Si Chen Xingming Zhang Key Laboratory of Regional Geography Beijing Normal University Beijing China Beijing Normal University Beijing Beijing CN

ISBN: (纸本)9781612848495

Area properties of mapping region has important impact on expressive effects of color grading symbol, which is mainly reflected in two aspects: firstly, color's area proportion in mapping region will affect the strength of visual impact from color, which can influence maps' clarity and comfort; secondly, area difference between different classes will affects visual perception caused by original color grading symbols, which can cause visual illusion. Based on China's provincial area model, this paper explores how to recognize the problems caused by area difference, and provide thought of auto-adjustment of traditional color grading symbol. Then the paper realizes the method using Visual C# and Supermap Object to realize a system having the function of the auto - adjustment of the map color.

关键词： Image color analysis visualization Geographic Information Systems Color Visual perception Presses data visualization

来源：评论

学校读者我要写书评

暂无评论

Effectiveness of visual analytics in supporting the reasoning on Vehicular Ad-Hoc Networks (poster)

Effectiveness of visual analytics in supporting the reasonin...

引用

IEEE Vehicular Networking conference (VNC)

作者： Daniele Brevi Hector Agustin Cozzetti Riccardo Scopigno Qing Xu BWA Laboratory (Broadband Wireless Access) Istituto Superiore Mario Boella Turin Italy School of Computer Science and Technology Tianjin University TJU China

ISBN: (数字)9781467300476

ISBN: (纸本)9781467300490

In the last years, a huge effort has been devoted to the improvement of simulation tools for Vehicular Ad-Hoc Networks (VANETs). However, one gap still needs to be filled: tools supporting the precise comprehension of the achieved numerical results, are not available yet; in fact, simulation platforms usually lead to quantitative figures which can be investigated only by statistics. Conversely, the simulation outputs are huge and depend on several aspects - such as mobility and position-dependent phenomena; consequently, they are particularly difficult to be comprehensively understood. While this aspect may seem negligible, it can strongly hamper the usability of the results. It is then envisioned the possibility to boost the analysis of network simulations by means of interactive tools. VisMagna is a visualization tool, specifically meant to support the understanding of complex VANET scenarios. The paper introduces it and shows it at work, highlighting the deeper understanding enabled by it.

关键词： Protocols data visualization Multiaccess communication visualization Animation Synchronization

来源：评论

学校读者我要写书评

暂无评论

RECENT IMPROVEMENTS IN DISPLAY AND analysis OF NDE data AT NASA

引用

AIP conference Proceedings 2011年第1期1335卷 1605-1612页

作者： D. J. Roth R. W. Rauser A. Abdul‐Aziz R. Cotton E. Burke S. Zhang M. Marsh B. A. Davis G. F. Studor aNASA Glenn Research Center Cleveland OH 44135 bUniversity of Toledo Toledo OH 43606‐3390 cCleveland State University 2121 Euclid Avenue Cleveland OH 44115‐2226 dSimpleware Rennes Drive Exeter EX4 4RN UK eNASA Langley Research Center Hampton VA 23681‐2199 fVisualization Sciences Group 15 New England Executive Park Burlington MA 01803 gNASA Johnson Space Center Houston TX 77058

This talk reviews several recent NDE data visualization and analysis improvements implemented at NASA Glenn Research Center. Examples will be shown in the areas of X‐ray computed tomography and waveform‐based NDE. Emphasis is on methods that are most useful not only for the NDE professional analyzing the data but also for sharing of the data with customers such as material processors, testers, and modelers who need to use the data for various engineering decisions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Visual Group Identification Method of Technical Competitors Using LinLog Graph Clustering Algorithm

Visual Group Identification Method of Technical Competitors ...

引用

2011 IEEE International conference on Computer Science and Automation Engineering(CSAE 2011)

作者： HAN Hong-qi,AN Xiaomi Key Laboratory of data Engineering and Knowledge Engineering (Renmin University of China),Ministry of Education School of Information Resource Management Beijing 100872,China ZHU Donghua,WANG Xuefeng School of Management and Economics Beijing Institute of Technology Beijing 100872,China

visualization technique is a powerful method used by science and technology intelligence analysis experts to identify technical competitor *** visualization methods tend to create graphs meeting the aesthetic criteria instead of finding better clusters,and their analysis results may provide misleading information.A process model of technical group identification method was presented using LinLog graph clustering algorithm to find better competitor *** the model,technical similarity value of each pair of competitors is measured based on their R&D output in sub-fields,and two competitors have a link when they have high similarity value;LinLog algorithm,which is aimed at producing better clusters,was employed to layout graph with competitors as nodes,their links as edges and technology similarity values as weights of *** results show the efficiency of presented method.

关键词： Group analysis visualization Patent analysis LinLog Graph Clustering Algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：