As digital libraries make the dissemination of research publications easier, they also enable the propagation of invalid or unreliable knowledge. Examples of relevant problems include: retraction and inadvertent citat...
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ISBN:
(纸本)9781665417709
As digital libraries make the dissemination of research publications easier, they also enable the propagation of invalid or unreliable knowledge. Examples of relevant problems include: retraction and inadvertent citation and reuse of retracted papers [1], [2]; propagation of errors in literature and scientific databases [3], [4]; non-reproducible papers; known domain-specific issues such as cell line contamination [5]; bias in research datasets and publications [6]–[8]; systematic reviews that arrive at different conclusions about the same question at the same time [9], [10]. The digital environment facilitates broad interdisciplinary reuse beyond the originating scientific community; thus, marking known problems and tracing the impact on dependent and follow-on works is particularly important (but still under-addressed). Further, context-specific information inside a paper may not be immediately reusable when extracted by automated processes, leading to apparent contradictions [11]. Current mitigating approaches use the underlying reasoning for information retrieval [12], [13], develop new infrastructures analyzing the reasoning [14]–[16] or certainty [17] of statements, or use visualization to highlight possible discrepancies [10], [15].
In this paper, we have developed a novel framework to enable more effective investigation of large-scale news video database via knowledge visualization. To relieve users from the burdensome exploration of well-known ...
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ISBN:
(纸本)9781424416592
In this paper, we have developed a novel framework to enable more effective investigation of large-scale news video database via knowledge visualization. To relieve users from the burdensome exploration of well-known and uninteresting knowledge of news reports, a novel interestingness measurement for video news reports is presented to enable users to find news stories of interest at first glance and capture the relevant knowledge in large-scale video news databases efficiently. Our framework takes advantage of both automatic semantic video analysis and human intelligence by integrating with visualization techniques on semantic video retrieval systems. Our techniques on intelligent news video analysis and knowledge discovery have the capacity to enable more effective visualization and exploration of large-scale news video collections. In addition, news video visualization and exploration can provide valuable feedback to improve our techniques for intelligent news video analysis and knowledge discovery.
Big data analysis is often seen as a complex process for processing large sets of data to uncover hidden information and patterns. This information can then be used by different groups of people to make decisions, to ...
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Dietary supplements (DS) are widely used. However, consumers know little about the safety and efficacy of DS. There is a growing interest in accessing health information online;however, online health information, espe...
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ISBN:
(纸本)9781538691380
Dietary supplements (DS) are widely used. However, consumers know little about the safety and efficacy of DS. There is a growing interest in accessing health information online;however, online health information, especially information on DSs, is scattered with varying levels of quality. We prototyped a web application, ALOHA, with interactive graph-based visualizations to facilitate users' browsing of the integrated DIetary Supplement Knowledge base (iDISK) curated from scientific resources, following an iterative user-centered design (UCD) process.
The advent of the Big Data challenge has stimulated research on methods and techniques to deal with the problem of managing data abundance. As a result, effective sense-making of semantically rich and big datasets has...
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ISBN:
(纸本)9781467382731
The advent of the Big Data challenge has stimulated research on methods and techniques to deal with the problem of managing data abundance. As a result, effective sense-making of semantically rich and big datasets has received a lot of attention, and new search approaches, such as Exploratory Computing (EC), have seen the light. In this paper we present IQ4EC, a system for data exploration inspired by EC, that supports users in the inspection of huge amounts of relational data through a step-by-step process, providing feedback based on approximate, intensional information expressed in terms of association rules. At each step of the process, the users can choose a portion of data to examine, and the system guides them to the next step by providing synthetic information and visualization of the resulting dataset.
visually integrating the initiation and developmental processes of organisms, we might reveal new causalities in biological data. Here we present an integrated visualization system for a causality network constructed ...
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ISBN:
(纸本)9781538614242
visually integrating the initiation and developmental processes of organisms, we might reveal new causalities in biological data. Here we present an integrated visualization system for a causality network constructed from phenotypic developmental characters and their related scientific literature. To obtain the phenotypic characters, we applied bio-imaging informatics techniques to the data of wet experiments. The phenotypic character network was visually rendered in the CausalNet system, which provides both explanatory and verification visualization functions. Statistical analysis and scientific literature mining proved useful for determining the mechanisms underlying the phenotypic character network. The validity of the system was confirmed in an application example and expert feedback on the developmental process of the nematode Caenorhabditis gans. The discussed methodology is applicable to other multicellular organisms.
Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of engineers and scientists in order to study remote environments. The most complex and successful of t...
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ISBN:
(纸本)0780392981
Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of engineers and scientists in order to study remote environments. The most complex and successful of these recent projects is the Mars Exploration Rover mission. The Computational Sciences Division at NASA Ames Research Center delivered a 3D visualization program, Viz, to the AHR mission that provides an immersive, interactive environment for science analysis of the remote planetary surface. In addition, Ames provided the Athena Science Team with high-quality terrain reconstructions generated with the Ames Stereo-pipeline. The on-site support team for these software systems responded to unanticipated opportunities to generate 3D terrain models during the primary AHR mission. This paper describes Viz, the Stereo-pipeline, and the experiences of the on-site team supporting the scientists at JPL during the primary AHR mission.
Visualizing complex scientific data and models in 2D can be challenging. The result can be hard to interpret and understand for the general audience, and the model accuracy hard to evaluate even for the experts. To ad...
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ISBN:
(纸本)9781728113777
Visualizing complex scientific data and models in 2D can be challenging. The result can be hard to interpret and understand for the general audience, and the model accuracy hard to evaluate even for the experts. To address these problems, we created a workflow that translates data of an ecological model, LANDIS-II, into a high-fidelity 3D model in virtual reality (VR). We combined ecological modeling, analytical modeling, procedural modeling, and VR, to allow users to experience a forest in northern Wisconsin (WI), United States, under two climate scenarios. Users can explore and interact with the forest under different climate scenarios, explore the impacts of climate change on different tree species, and retrieve information from a 3D tree database. The VR application can be used as an educational tool for the general public, and as a model checking tool by researchers.
SoftAnal and SoftRepo are tools developed to provide repository services to a Viennese software house - Software Data Service - that has developed a series of financial service software systems now in the evolution ph...
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ISBN:
(纸本)0769511902
SoftAnal and SoftRepo are tools developed to provide repository services to a Viennese software house - Software Data Service - that has developed a series of financial service software systems now in the evolution phase. Repository services include automated software measurement, automated code inspection, automated post-documentation, automated generation of test cases, impact analysis, evolution project estimation and software structure visualization.
Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operati...
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Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. Visual Analytics techniques have potential to considerably enhance the knowledge discovery process and increase the detection and prediction accuracy of financial fraud detection systems. Thus, we propose EVA, a Visual Analytics approach for supporting fraud investigation;fine-tuning fraud detection algorithms, and thus. reducing false positive alarms.
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