• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.6
• /
• pp.2801-2816
• /
• 2016

Owing to their low scalability, weak support on big data, insufficient data collaborative analysis and inadequate situational awareness, the traditional methods fail to meet the needs of the security data analysis. This paper proposes visualization methods to fuse the multi-source security data and grasp the network situation. Firstly, data sources are classified at their collection positions, with the objects of security data taken from three different layers. Secondly, the Heatmap is adopted to show host status; the Treemap is used to visualize Netflow logs; and the radial Node-link diagram is employed to express IPS logs. Finally, the Labeled Treemap is invented to make a fusion at data-level and the Time-series features are extracted to fuse data at feature-level. The comparative analyses with the prize-winning works prove this method enjoying substantial advantages for network analysts to facilitate data feature fusion, better understand network security situation with a unified, convenient and accurate mode.

• Journal of Internet Computing and Services
• /
• v.17 no.4
• /
• pp.69-77
• /
• 2016

Recently, the importance of visual analytics has been recognized in the field of business intelligence. From the view of business intelligence, visual analytics aims for acquiring valuable insights for decision making by interactively visualizing a variety of business information. In this paper, we propose a treemap-based method for visualizing work-sharing relationships among business process performers. A work-sharing relationship is established between two performers who jointly participate in a specific activity of a business process and is an important factor for understanding organizational structures and behaviors in a process-centric organization. To this end, we design and implement a treemap-based visualization tool for representing work-sharing relationships as well as basic hierarchical information in business processes. Finally, we evaluate usefulness of the proposed visualization tool through an operational example using XPDL (XML Process Definition Language) process models.

• Science of Emotion and Sensibility
• /
• v.9 no.spc3
• /
• pp.209-224
• /
• 2006

Hierarchy which is often named as the tree-structure is used to reduce complexity and show primitive structures of complicated information. This paper aims at explaining information-visualization methods using hierarchies in multimedia domains and prospecting the possible applications by examining how they affect the user's tasks involved in information-seeking activities. As a result, four types of information visualization methods named Treemap, Hyperbolic, Cone Tree and DOI Tree employed in multimedia domain, are presented and pros and cons of each method are explained in this paper. Another important part is defining the core tasks and other related-tasks in information-seeking activities, such as, overview, zoom, filter, details-on-demand, relate, history, and extract. Followings are major findings. Treemap uses 'overview' as the core task, which makes user to gain a overall meaning of the whole information cluster. Hyperbolic and DOI Tree apply 'Boom' task through the function of focus+context or by the function of meaningful scaling to magnify or downsize each node. Cone Tree, also, makes the information organizer to classify the patterns of information acquired in the process of users' information-seeking activities by using 'extract' task. Through this study, it is finally found out that the information-visualization methods using hierarchies in multimedia domains should incorporate the wide variety of functional needs related to users' information-seeking behaviors beyond the visual representation of information.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.1036-1041
• /
• 2005

Treemaps, a space filling visualization technique, displays a massive data set of hierarchical data interactively on a single computer screen by mapping it to a matrix of rectangles. It allows users to visually inspect and manipulate data to find new relationships or discrepancies that are to difficult to find using traditional techniques. This paper applies treemaps to the evaluation of highway project bids, which contain hundreds or thousands of elements arranged in a hierarchical structure. Through a case study, treemaps are shown to be a potentially effective tool for bid evaluation by both contractors and State or Federal highway officials.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.5 no.2
• /
• pp.21-28
• /
• 2009

This paper proposes RCBT(Reduced Compact Binary trie) to correct faults of CBT (Compact Binary trie). First, in the case of CBT, a compact structure was tried for the first time, but as the amount of data was increasing, that of inputted data gained and much difficulty was experienced in insertion due to the dummy nodes used in balancing trees. On the other hand, if the HCBT realized hierarchically, given certain depth to prevent the map from increasing onthe right, reached the depth, the method for making new trees and connecting to them was used. Eventually, fast progress could be made in the inputting and searching speed, but this had a disadvantage of the storage space becoming bigger because of the use of dummy nods like CBT and of many tree links. In the case of RCBT in this thesis, a capacity is increased by about 60% by completely cutting down dummy nods.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.4
• /
• pp.11-19
• /
• 2007

This paper proposes RCB(Reduced Compact Binary) tie to correct faults of both CB(Compact Binary) tie and HCB(Hierarchical Compact Binary) trie. First, in the case of CB trie, a compact structure was tried for the first time, but as the amount of data was increasing, that of inputted data gained and much difficulty was experienced in insertion due to the dummy nods used in balancing trees. On the other hand, if the HCB trie realized hierarchically, given certain depth to prevent the map from increasing on the right, reached the depth, the method for making new trees and connecting to them was used. Eventually, fast progress could be made in the inputting and searching speed, but this had a disadvantage of the storage space becoming bigger because of the use of dummy nods like CB trie and of many tree links. In the case of RCB trie in this thesis, the tree-map could be reduced by about 35% by completely cutting down dummy nods and the whole size by half, compared with the HCB trie.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.109-122
• /
• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.