This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection *** reduce the volume of bigdata and minimize model training time(Tt)while maintai...
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This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection *** reduce the volume of bigdata and minimize model training time(Tt)while maintaining data *** contributed to meeting the challenges of big data visualization using the embedded method based“Select from model(SFM)”method by using“Random forest Importance algorithm(RFI)”and comparing it with the filter method by using“Select percentile(SP)”method based chi square“Chi2”tool for selecting the most important features,which are then fed into a classification process using the logistic regression(LR)algorithm and the k-nearest neighbor(KNN)***,the classification accuracy(AC)performance of LRis also compared to theKNN approach in python on eight data sets to see which method produces the best rating when feature selection methods are ***,the study concluded that the feature selection methods have a significant impact on the analysis and visualization of the data after removing the repetitive data and the data that do not affect the *** making several comparisons,the study suggests(SFMLR)using SFM based on RFI algorithm for feature selection,with LR algorithm for data *** proposal proved its efficacy by comparing its results with recent literature.
In this paper, an in-depth study on the quantification of influencing factors and big data visualization of key monitoring indicators in the refined oil products market is carried out through fuzzy mathematical method...
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In this paper, an in-depth study on the quantification of influencing factors and big data visualization of key monitoring indicators in the refined oil products market is carried out through fuzzy mathematical methods, and a system for quantifying influencing factors and big data visualization of key monitoring indicators in the refined oil products market with the fuzzy mathematical background is designed and implemented. The system realizes the functions of flow visualization, attack visualization, target tracking visualization, etc., and optimizes the system from the perspectives of performance and visualization effect. It achieves the display and interaction of multi-dimensional data in space and time with multiple views, angles, and dimensions. data tagging and data correlation for key aspects of the product production process are realized through fuzzy mathematics and other means, and a quality traceability system for the manufacturing industry is realized on this basis, through which the data of some key stages of the product production process can be displayed retrospectively. The study proves that the business model of refined oil logistics platform based on value network can significantly improve the user's perceived value and benefit all parties within the value network, realizing the complementary advantages of refined oil production enterprises and logistics platform companies, improving the efficiency of enterprise's logistics and maximizing the profit of each subject within the value network to achieve profitability for all parties.
The progression of Internet of Things (IoT) has resulted in generation of huge amount of data. Effective handling and analysis of such big volumes of data proposes a crucial challenge. Existing cloud-based frameworks ...
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The progression of Internet of Things (IoT) has resulted in generation of huge amount of data. Effective handling and analysis of such big volumes of data proposes a crucial challenge. Existing cloud-based frameworks of big data visualization are rising costs for servers, equipment, and energy consumption. There is a need for a green solution targeting lesser cost and energy consumption with tamper-proof record-keeping, storage, and interactive visualization with only demanded data. We have proposed a Blockchain-based Green big data visualization (BGbV) solution using Hyperledger Sawtooth for optimum utilization of organization resources. BGbV will support current distributed datavisualization platforms and guarantee benefits like security and data availability with lesser storage costs. It helps reduce costs by utilizing small resources that are already available and consume less energy, making it an environmentally friendly solution.
Purpose In the digital age, the use of data and analytical capabilities to guide business decisions and operations plays a strategic role for organizations to gain competitive advantage (CA). However, the paths by whi...
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Purpose In the digital age, the use of data and analytical capabilities to guide business decisions and operations plays a strategic role for organizations to gain competitive advantage (CA). However, the paths by which analytical capabilities convey their effect to CA are not yet fully known and few studies address the role of behavioral and cultural aspects of related of analytical capabilities. The purpose of this paper is to analyze how data-driven culture (DDC) and business analytics (BA) affect CA, considering the mediating effects of big data visualization (BDV) and organizational agility (OA). Design/methodology/approach A survey was conducted with 173 managers who are BDV and BA users in Brazilian organizations of various economic segments. The data were analyzed through structural equation modeling and mediation tests. Findings The evidence indicates that DDC and BDV are antecedents of BA. The following complementary mediations were discovered: BDV in the relationship between DDC and BA;BA in the relationship between DDC and CA;and OA in the relationship between BA and CA. It was also discovered that OA explains the transmission of most of the effect of BA to CA. Practical implications This study can help organizations to understand the importance of cultural and behavioral aspects related to the use of the analytical capabilities. Thereby, managers can establish policies and strategies to extract value from data and leverage business agility and competitiveness through use BDV and BA. Originality/value This study fills an important research gap by developing an original research model and discussing empirical evidence on how DDC and BA affect CA, considering the mediating effects of BDV and OA.
Currently, bigdata Analytics help educators better analyze students and monitor their progress and likelihood of success. The online learning experience applies to the experiences in the online computer-mediated digi...
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Currently, bigdata Analytics help educators better analyze students and monitor their progress and likelihood of success. The online learning experience applies to the experiences in the online computer-mediated digital system to collect information. An essential part of education training programs is challenging and effectively implemented between teachers and students in the online learning feedback system. Hence, a big data visualization assisted Multimodal Feedback Framework (BDVMFF) is proposed to boost students' confidence, self-consciousness, and motivation in the online learning platform. The BDVMFF offers the teacher a digital workflow to effectively exchange both the writing and the input to use multimodal feedback effectively. This system provides teachers and students with an effective and straightforward digital learning environment. The simulation results of BDVMFF show the highest performance ratio (97.9%), the efficiency ratio (96.1%), the grade analysis ratio (93.5%), the computation ratio (95.3%), and the lowest response time compared to existing methods.
In the era of bigdata, people's visual needs for data expression are increasing. In order to achieve better bigdata display effects, this article introduced the use of text clustering algorithms to achieve data ...
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ISBN:
(纸本)9781450388597
In the era of bigdata, people's visual needs for data expression are increasing. In order to achieve better bigdata display effects, this article introduced the use of text clustering algorithms to achieve data crawling and Echarts technology to realize big data visualization. This system used mvvm's architecture and vue framework development platform, ThinkPHP was used as the background framework, and ES6 related technologies and specifications were used for application development. This system used Echarts, IView, GIS technology and JavaScript development methods to demonstrate economic bigdata module functions on the web side; Applied CSS3, HTML5, GIS technology to implement project achievement module and university alliance module; Applied Echarts, HTML5, JS function library technology to achieve national information module. This system used stored procedure, database index optimization technology to achieve rapid screening of massive data, and dynamically update and displayed related data through two-way data binding. This system combined real-time location technology with GIS technology to measure the distance between the user and the destination, and automatically plan the tour route to provide related services. This system can provide feasibility suggestions for strategic researchers or experts in related areas of the “Belt and Road”, and provide theoretical basis and technical support.
A tremendous amount of data comes with a vast amount of knowledge. Decent use of the persistent information can assist to overcome provocations and support to establish further sophisticated judgment. data visualizati...
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ISBN:
(纸本)9781538648384
A tremendous amount of data comes with a vast amount of knowledge. Decent use of the persistent information can assist to overcome provocations and support to establish further sophisticated judgment. datavisualization techniques are authenticated scientifically as thousand times reliable rather than textual representation. The premature datavisualization system met some difficulties and there has some solution for handle this kind of big quantity of data. data science used two distinct languages Python and R to visualize bigdata undeviatingly. There also have a lot of tools in operating business. This paper is focused on the visualization technique of Python and R. R appears including the extraordinary visualization library alike ggplot2, leaflet, and lattice to defeat the provocation of the extensive volume. Python has several particular libraries for datavisualization. Commonly they are Bokeh, Seaborn, Altair, ggplot and Pygal. Also, with most modern, secure and powerful zero coding GUI's accessories to describe big data visualization for genuine recognition with practical determination. Method and process of visual description of data are significant to recover specific knowledge from the large-scale dataset.
In the era of bigdata, a great attention deserves the visualization of large data sets. Among the main phases of the data management's life cycle, i.e., storage, analytics and visualization, the last one is the m...
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ISBN:
(纸本)9789897582554
In the era of bigdata, a great attention deserves the visualization of large data sets. Among the main phases of the data management's life cycle, i.e., storage, analytics and visualization, the last one is the most strategic since it is close to the human perspective. The huge mine of data becomes a gold mine only if tricky and wise analytics algorithms are executed over the data deluge and, at the same time, the analytic process results are visualized in an effective, efficient and why not impressive way. Not surprisingly, a plethora of tools and techniques have emerged in the last years for big data visualization, both as part of data Management Systems or as software or plugins specifically devoted to the datavisualization. Starting from these considerations, this paper provides a survey of the most used and spread visualization tools and techniques for large data sets, eventually presenting a synoptic of the main functional and non-functional characteristics of the surveyed tools.
Nowadays,thanks to new technologies,we are observing an explosion of data in different fields such as clinical,environmental and so *** this context,a typical example of the well-known bigdata problem is represented ...
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Nowadays,thanks to new technologies,we are observing an explosion of data in different fields such as clinical,environmental and so *** this context,a typical example of the well-known bigdata problem is represented by *** this work,we propose an innovative platform for managing the oceanographic *** specifically,we present two innovative visualization techniques:general overview and site specific *** prove the goodness of the proposed system in terms both of performance and user experience.
The explosion of information has led to the proliferation of bigdata as an influential business and research domain. data center infrastructure management is a sector largely affected by bigdata, however the visuali...
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ISBN:
(纸本)9783319585215;9783319585208
The explosion of information has led to the proliferation of bigdata as an influential business and research domain. data center infrastructure management is a sector largely affected by bigdata, however the visualization of, and interaction with, bigdata in the context of a data center room is a challenging endeavor. This paper presents the iterative design and development of a 3D data Centre visualization application featuring gesture-based interaction with a high resolution large screen display. As result of the design iterations three distinct system versions were developed, evolving the supported functionality, the User Interface and the interaction methods. The paper presents the evolution of the system, the results of an expert-based evaluation which was carried out during the development life-cycle, as well as the challenges faced and lessons learned regarding the User Experience design of a bigdata application deployed in a large display, supporting gestural interaction.
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