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A temporal visualization method for dynamically analyzing networked information

IP.com Disclosure Number: IPCOM000031586D
Original Publication Date: 2004-Sep-30
Included in the Prior Art Database: 2004-Sep-30
Document File: 6 page(s) / 117K

Publishing Venue

IBM

Abstract

Networked information structure is one important data type. As the amount of information in these structures increases exponentially, it becomes increasingly difficult for users to find information and increasingly easy for users to be overloaded with information. Information visualization enables people to deal with all of this information by taking advantage of our innate visual perception capabilities. In this disclosure, we proposed a temporal visualization method for dynamically analyzing networked information at different time points. In this method, two distinct networks at different time points are compared, and then their similarities and dissimilarities are visualized. Based on this, the user can have an overview of the evolution of the network structure.

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A temporal visualization method for dynamically analyzing networked information

Background:

Networked information structure is one important data type. We are surrounded by networked information of all kinds: social network, knowledge network, computer network, ecological network, economic network, and so on. As the amount of information in these structures increases exponentially, it becomes increasingly difficult for users to find information and increasingly easy for users to be overloaded with information. Information visualization enables people to deal with all of this information by taking advantage of our innate visual perception capabilities.

There has been substantial research dedicated to visualizing this kind of information as graphs [Herman2000, Bénédicte1999]. However, these works focus on visualizing static networked information. Static visualization presents us with information about the current networked structure. However, with this kind of visualization, the user can only analyze the network at one time point. In fact, comparison between different time points provides more useful information/knowledge for finding patterns, recognizing gaps, and so on. However, little work has been done so far to compare networked information at different time points.

In this disclosure, we proposed a temporal visualization method for dynamically analyzing networked information at different time points. In this method, two distinct networks at different time points are compared, and then their similarities and dissimilarities are visualized. Based on this, the user can have an overview of the evolution of the network structure.

References:

[Herman2000] Herman I, Melancon G, Marshall MS. Graph visualization and navigation in information visualization: a survey. IEEE Transactions on Visualization and Computer Graphics, 6(1): 24-43, 2000. [Bénédicte1999] Bénédicte LG, Michel S. Navigation in huge information hierarchies - application to network management. Proceedings of the ACM Workshop on New Paradigms in Information Visualization and Manipulation, pp. 56-61, 1999.

Summary of invention:

In this disclosure, a novel visualization method for analyzing networked information at two time points is proposed. The goal is to facilitate the analysis of networked information, such as social network.

Figure 1 depicts the comparison of networked information at two different time points. We assume that the information/data about the networked structure has been saved with time. For example, for an enterprise social network, the changes of project, staff, and other related resources about an enterprise will be recorded. When a user wants to compare the network structure (social networks) at different time points, he will input the two time points with some UI method and then corresponding information/data about the social networks will be retrieved.

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Input 2 time points

    Retrieve corresponding networked information

Visualize and comp...