Analysts are increasingly drowning in a flood of information. KBSI has addressed this challenge through the Intelligence Product Mosaic (TM) (IPM) analysis, visualization, and reporting tool that exploits the cognitiv...
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ISBN:
(纸本)9781479962273
Analysts are increasingly drowning in a flood of information. KBSI has addressed this challenge through the Intelligence Product Mosaic (TM) (IPM) analysis, visualization, and reporting tool that exploits the cognitive strength of analysts and enables them to discover information intuitively and quickly. This article provides an overview of the IPM analytic process and the visualizations that were used to enable better end user understanding of the information derived from multi-source text data. The main benefits of the IPM tool described in this paper include (i) significant reductions in 'data-to-decision' time through the use of semantic and collaborative visualanalytics techniques and (ii) significant increases in the ability to exploit information and knowledge embedded within data through the use of semantic methods.
The integration of the Internet of Things (IoT) in Physical Education (PE) has become a burgeoning area of research, driven by advancements in wearable technologies, smart environments, and data analytics. This study ...
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Crime forecasting is a critical endeavor aimed at preventing future criminal actions, specifically the rising rate of violence against women in India. This study proposes the model to predict crimes committed against ...
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ISBN:
(数字)9798331521691
ISBN:
(纸本)9798331521707
Crime forecasting is a critical endeavor aimed at preventing future criminal actions, specifically the rising rate of violence against women in India. This study proposes the model to predict crimes committed against women using data from the National Crime Records Bureau's (NCRB) monthly crime report. The dataset encompasses district and state-wise crime activities from 2001 to 2014. The proposed work objectives are identifying factors influencing these crimes and developing predictive models using machine learning (ML). The study employs Exploratory Data Analysis (EDA), to enhance the predictive power of the models. The suggested study uses XGBoost, Random Forest (RF), and Neural Network (NN). The neural network algorithm outperforms the Random Forest and XGBoost techniques among these three. The Random Forest algorithm has the worst performance. After comparing the accuracies of various methods, such as XGBoost (92%), and Random Forest (89.84%) classifiers using imbalanced datasets (without employing Synthetic Minority Oversampling Technique (SMOTE) technique), it was found that the neural network algorithm (95.81%) delivers the highest accuracy. This study looks at model accuracies and finds that, after applying the SMOTE algorithm, neural network algorithms performed best, with an accuracy of 96.76%, outperforming the accuracies of the remaining models, which included the Random Forest (93.08%) and XG-Boost (95%).
vast2014 Mini-Challenge 3 requires to identify the events for further investigation on the disappearance of GAStech employees from the streaming data. To tackle this mini-challenge, we proposed a visualanalytics too...
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ISBN:
(纸本)9781479962273
vast2014 Mini-Challenge 3 requires to identify the events for further investigation on the disappearance of GAStech employees from the streaming data. To tackle this mini-challenge, we proposed a visualanalytics tool. In this paper, we summarize the design and implementation of our tool. Besides, we illustrate how we use the tool to indicate the events.
The 2014vast mini-challenge 1 asked participants to summarise the structure of a terrorist organisation and how it has changed over time, reconstruct the chain of events of a kidnapping and to provide two possible ex...
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ISBN:
(纸本)9781479962273
The 2014vast mini-challenge 1 asked participants to summarise the structure of a terrorist organisation and how it has changed over time, reconstruct the chain of events of a kidnapping and to provide two possible explanations.
In this paper, we propose a web-based interactive visual analytic system effective for revealing the trajectory patterns. We describe the analysis approach with the data of MC1 of the vast challenge 2017.
ISBN:
(纸本)9781538631638
In this paper, we propose a web-based interactive visual analytic system effective for revealing the trajectory patterns. We describe the analysis approach with the data of MC1 of the vast challenge 2017.
In this paper, we describe the tools and the analysis pipeline we used in order to create a data structure out of the given data. Afterwards, we introduce a workflow used to find answers to the questions of vast Chall...
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ISBN:
(纸本)9781479962273
In this paper, we describe the tools and the analysis pipeline we used in order to create a data structure out of the given data. Afterwards, we introduce a workflow used to find answers to the questions of vast Challenge 2014 MC1. Most of the processes presented in the following have been used solely to create, refine a graph (node-link diagram), which is the foundation for everything we did in this mini challenge.
The vast 2014 Mini-challenge 2 [2] provided a set of GPS vehicle tracking and credit card transaction data with the aim of inferring behaviour of those using the vehicles and credit cards. In particular it required de...
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ISBN:
(纸本)9781479962273
The vast 2014 Mini-challenge 2 [2] provided a set of GPS vehicle tracking and credit card transaction data with the aim of inferring behaviour of those using the vehicles and credit cards. In particular it required designing or applying a visualanalytics system to identify typical behaviours with which atypical, suspicious activity could be contrasted. It is an example of the more general case of inferring behaviour from movement records (e.g., from mobile devices [6] or public bikeshare schemes [1]). In this brief paper we summarise the design taken to address the particular vast challenge while proposing a general approach to movement-based behaviour detection.
We present our process and analysis for vast 2014 Mini Challenge 1 and 2, which integrate an off-the-shelf tool, Jigsaw, rapid web-based visualization prototyping using D3, and analytics-based visualizations using Mat...
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ISBN:
(纸本)9781479962273
We present our process and analysis for vast 2014 Mini Challenge 1 and 2, which integrate an off-the-shelf tool, Jigsaw, rapid web-based visualization prototyping using D3, and analytics-based visualizations using Matlab.
Gaining insights from different heterogeneous data sources is one of the biggest challenges in decision making support. The large volumes of data can only be combined by sophisticated automatic methods. However, unexp...
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ISBN:
(纸本)9781479962273
Gaining insights from different heterogeneous data sources is one of the biggest challenges in decision making support. The large volumes of data can only be combined by sophisticated automatic methods. However, unexpected patterns can only be identified with the help of human intuition. In this paper, we present our visualanalytics work-flows and tools to process heterogeneous data such as social networks, text streams, and geo-temporal data. We apply these tools on the vast Challenge data and present our findings and assumptions that we identified in our analysis.
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