Visualization of individual's knowledge by analyzing the citation networks

Visual analysis of knowledge domain is an emerging field of study as science is highly dynamic and constantly evolving. Behind the scene, a knowledge domain is formed and contributed by enormous researchers' publications that describe the common subject of the domain. There is large number of significant activities have been carried out to visualize and identify the knowledge domains of research projects, groups and communities. However, the research on visualizing the knowledge structure at individual level is relative inactive. It is difficult to track down the individual's contribution to the subject and the degree of the knowledge they possess. In this paper, we are attempting to visualize the individual's knowledge structure by analyzing the citation and co-authorship relational structures. We try to analyze and map author's documents to the knowledge domains. By mapping the documents to knowledge domain, we obtain the skeleton of knowledge structure of an individual. Then, we apply the visualization technique to present the result. © 2007 IEEE

CLPGUI: a generic graphical user interface for constraint logic programming over finite domains

CLPGUI is a graphical user interface for visualizing and interacting with constraint logic programs over finite domains. In CLPGUI, the user can control the execution of a CLP program through several views of constraints, of finite domain variables and of the search tree. CLPGUI is intended to be used both for teaching purposes, and for debugging and improving complex programs of realworld scale. It is based on a client-server architecture for connecting the CLP process to a Java-based GUI process. Communication by message passing provides an open architecture which facilitates the reuse of graphical components and the porting to different constraint programming systems. Arbitrary constraints and goals can be posted incrementally from the GUI. We propose several dynamic 2D and 3D visualizations of the search tree and of the evolution of finite domain variables. We argue that the 3D representation of search trees proposed in this paper provides the most appropriate visualization of large search trees. We describe the current implementation of the annotations and of the interactive execution model in GNU-Prolog, and report some evaluation results.Comment: 16 pages; Alexandre Tessier, editor; WLPE 2002, http://xxx.lanl.gov/abs/cs.SE/020705

Linguistic Geometries for Unsupervised Dimensionality Reduction

Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimensionality and visualize the low dimensional embedding as a 2-D or 3-D scatter plot. In this paper we explore dimensionality reduction methods that draw upon domain knowledge in order to achieve a better low dimensional embedding and visualization of documents. We consider the use of geometries specified manually by an expert, geometries derived automatically from corpus statistics, and geometries computed from linguistic resources.Comment: 13 pages, 15 figure

How can heat maps of indexing vocabularies be utilized for information seeking purposes?

The ability to browse an information space in a structured way by exploiting similarities and dissimilarities between information objects is crucial for knowledge discovery. Knowledge maps use visualizations to gain insights into the structure of large-scale information spaces, but are still far away from being applicable for searching. The paper proposes a use case for enhancing search term recommendations by heat map visualizations of co-word relation-ships taken from indexing vocabulary. By contrasting areas of different "heat" the user is enabled to indicate mainstream areas of the field in question more easily.Comment: URL workshop proceedings: http://ceur-ws.org/Vol-1311

Subjective information visualizations

Information Visualizations (InfoViz) are systems that require high levels of cognitive processing. They revolve around the notion of decoding and interpreting visual patterns in order to achieve certain goals. We argue that purely designing for the visual will not allow for optimum experiences since there is more to InfoViz than just the visual. Interaction is a key to achieving higher levels of knowledge. In this position paper we present a different perspective on the underlying meaning of interaction, where we describe it as incorporating both the visual and the physical activities. By physical activities we mean the physical actions upon the physical input device/s. We argue that interaction is the key element for supporting users’ subjective experiences hence these experiences should first be understood. All the discussions in this paper are based upon on going work in the field of visualizing the literature knowledge domain (LKDViz)