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Ubiquitous availability of human mobility data has opened up new possibilities to address a multitude of application domains. However, so far, the visual analysis of this data has been hindered by the limited ability to explore and query complex movement sequences and to create models that allow meaningful aggregation. To address this problem, this paper presents a novel analytical approach that allows...
Android's flexible communication model allows interactions among third-party apps, but it also leads to inter-app security vulnerabilities. Specifically, malicious apps can eavesdrop on interactions between other apps or exploit the functionality of those apps, which can expose a user's sensitive information to attackers. While the state-of-the-art tools have focused on detecting inter-app vulnerabilities...
There has been incredible growth of events over the internet in recent years. Google has become the giant source of knowledge for any event which has happened or happening over the internet. Some networking sites such as face book, micro blogging sites such as twitter are evolved with time and became the highly used sites over the internet. Various E-commerce websites such as Amazon, Ebay, Flipkart...
Public sentiment is regarded as an important measure for event detection, information security, policy making etc. Analyzing public sentiments relies more and more on large amount of multimodal contents, in contrast to the traditional text-based and image-based sentiment analysis. However, most previous works directly extract feature from image as the additional information for text modality and then...
The goal of this research is to design an e-learning content for student guidance based on 4MAT and ILS theory. This paper consists of seven parts as follows. Part one covers the learning activities. Part two is analysis of the learning activity. Part three is discussion of ILS and 4MAT. Part four is implementation of e-learning subjects. Part five is the search for experts to evaluate the learning...
Technology management data refers to all the data which is produced in the process of research and has witnessed rapid development in the literature. However, there lacks mapping and visualization of it in global scope. To identify the state and trend of technology management data, the paper uses Citespace to conduct a series of analysis, including the distribution of core authors, journal, countries...
Social graphs, representing online friendships among users, are one of the fundamental types of data for many applications, such as recommendation, virality prediction and marketing in social media. However, this data may be unavailable due to the privacy concerns of users, or kept private by social network operators, which makes such applications difficult. Inferring users' interests and discovering...
VINST is a system used to record all activities related to the incident and problem management in Volvo IT Belgium. In this VINST system, activities recorded in several attributes, such as serial number, change date and time, status, and any other attributes needed, which is stored in the event log. In these sequenced activities, there are some specific knowledge that is not explicitly described in...
Provenance captured from E-Science experimentation is often large and complex, for instance, from agent-based simulations that have tens of thousands of heterogeneous components interacting over extended time periods. The subject of study of my dissertation is the use of E-Science provenance at scale. My initial research studied the visualization of large provenance graphs and proposed an abstract...
With over 16 million tweets per hour, 600 new blog posts per minute, and 400 million active users on Facebook, businesses have begun searching for ways to turn real-time consumer-based posts into actionable intelligence. The goal is to extract information from this noisy, unstructured data and use it for trend analysis and prediction. Current practices support the idea that visual analytics (VA) can...
Dark web analysis is an important aspect in field of counter terrorism (CT). In the present scenario terrorist attacks are biggest problem for the mankind and whole world is under constant threat from these well-planned, sophisticated and coordinated terrorist operations. Terrorists anonymously set up various web sites embedded in the public Internet, exchanging ideology, spreading propaganda, and...
To make decisions about the long-term preservation and access of large digital collections, archivists gather information such as the collections' contents, their organizational structure, and their file format composition. To date, the process of analyzing a collection — from data gathering to exploratory analysis and final conclusions — has largely been conducted using pen and paper methods. To...
Sensitivity analysis is a powerful method for discovering the significant factors that contribute to targets and understanding the interaction between variables in multivariate datasets. A number of sensitivity analysis methods fall into the class of local analysis, in which the sensitivity is defined as the partial derivatives of a target variable with respect to a group of independent variables...
In this paper, we introduce a web mining solution to business intelligence to discover hidden patterns and business strategies from their customer and web data. We propose a new framework based on web mining technology. Web mining attempts to determine useful knowledge from secondary data obtained from the interactions of the users with the web.
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization system which greatly reduces the load on the users and makes the process of model initialization and refinement more efficient, problem-driven, and engaging. Utilizing a sequence segmentation task with a Hidden Markov Model...
Attack graphs play important roles in analyzing network security vulnerabilities, and previous works have provided meaningful conclusions on the generation and security measurement of attack graphs. However, it is still hard for us to understand attack graphs in a large network, and few suggestions have been proposed to prevent inside malicious attackers from attacking networks. To address these problems,...
Visual data mining can help in dealing with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process, through analysis the results of the information visualization, user can integrate the specialist knowledge with the data mining algorithm. This paper summarizes current visualization methods applied in data mining. Current...
During visual analysis, users must often connect insights discovered at various points of time. This process is often called ldquoconnecting the dots.rdquo When analysts interactively explore complex datasets over multiple sessions, they may uncover a large number of findings. As a result, it is often difficult for them to recall the past insights, views and concepts that are most relevant to their...
Latent Semantic Analysis (LSA) is a commonly-used method for automated processing, modeling, and analysis of unstructured text data. One of the biggest challenges in using LSA is determining the appropriate model parameters to use for different data domains and types of analyses. Although automated methods have been developed to make rank and scaling parameter choices, these approaches often make...
Visual analytics tools provide powerful visual representations in order to support the sense-making process. In this process, analysts typically iterate through sequences of steps many times, varying parameters each time. Few visual analytics tools support this process well, nor do they provide support for visualizing and understanding the analysis process itself. To help analysts understand, explore,...
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