Text mining with the WEBSOM

The emerging field of text mining applies methods from data mining and exploratory data analysis to analyzing text collections and to conveying information to the user in an intuitive manner. Visual, map-like displays provide a powerful and fast medium for portraying information about large collections of text. Relationships between text items and collections, such as similarity, clusters, gaps and outliers can be communicated naturally using spatial relationships, shading, and colors. In the WEBSOM method the self-organizing map (SOM) algorithm is used to automatically organize very large and high-dimensional collections of text documents onto two-dimensional map displays. The map forms a document landscape where similar documents appear close to each other at points of the regular map grid. The landscape can be labeled with automatically identified descriptive words that convey properties of each area and also act as landmarks during exploration. With the help of an HTML-based interactive tool the ordered landscape can be used in browsing the document collection and in performing searches on the map. An organized map offers an overview of an unknown document collection helping the user in familiarizing herself with the domain. Map displays that are already familiar can be used as visual frames of reference for conveying properties of unknown text items. Static, thematically arranged document landscapes provide meaningful backgrounds for dynamic visualizations of for example time-related properties of the data. Search results can be visualized in the context of related documents. Experiments on document collections of various sizes, text types, and languages show that the WEBSOM method is scalable and generally applicable. Preliminary results in a text retrieval experiment indicate that even when the additional value provided by the visualization is disregarded the document maps perform at least comparably with more conventional retrieval methods.reviewe

From Keyword Search to Exploration: How Result Visualization Aids Discovery on the Web

A key to the Web's success is the power of search. The elegant way in which search results are returned is usually remarkably effective. However, for exploratory search in which users need to learn, discover, and understand novel or complex topics, there is substantial room for improvement. Human computer interaction researchers and web browser designers have developed novel strategies to improve Web search by enabling users to conveniently visualize, manipulate, and organize their Web search results. This monograph offers fresh ways to think about search-related cognitive processes and describes innovative design approaches to browsers and related tools. For instance, while key word search presents users with results for specific information (e.g., what is the capitol of Peru), other methods may let users see and explore the contexts of their requests for information (related or previous work, conflicting information), or the properties that associate groups of information assets (group legal decisions by lead attorney). We also consider the both traditional and novel ways in which these strategies have been evaluated. From our review of cognitive processes, browser design, and evaluations, we reflect on the future opportunities and new paradigms for exploring and interacting with Web search results

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

ASTRAL PROJECTION: THEORIES OF METAPHOR, PHILOSOPHIES OF SCIENCE, AND THE ART O F SCIENTIFIC VISUALIZATION

This thesis provides an intellectual context for my work in computational scientific visualization for large-scale public outreach in venues such as digitaldome planetarium shows and high-definition public television documentaries. In my associated practicum, a DVD that provides video excerpts, 1 focus especially on work I have created with my Advanced Visualization Laboratory team at the National Center for Supercomputing Applications (Champaign, Illinois) from 2002-2007. 1 make three main contributions to knowledge within the field of computational scientific visualization. Firstly, I share the unique process 1 have pioneered for collaboratively producing and exhibiting this data-driven art when aimed at popular science education. The message of the art complements its means of production: Renaissance Team collaborations enact a cooperative paradigm of evolutionary sympathetic adaptation and co-creation. Secondly, 1 open up a positive, new space within computational scientific visualization's practice for artistic expression—especially in providing a theory of digi-epistemology that accounts for how this is possible given the limitations imposed by the demands of mapping numerical data and the computational models derived from them onto visual forms. I am concerned not only with liberating artists to enrich audience's aesthetic experiences of scientific visualization, to contribute their own vision, but also with conceiving of audiences as co-creators of the aesthetic significance of the work, to re-envision and re-circulate what they encounter there. Even more commonly than in the age of traditional media, on-line social computing and digital tools have empowered the public to capture and repurpose visual metaphors, circulating them within new contexts and telling new stories with them. Thirdly, I demonstrate the creative power of visaphors (see footnote, p. 1) to provide novel embodied experiences through my practicum as well as my thesis discussion. Specifically, I describe how the visaphors my Renaissance Teams and I create enrich the Environmentalist Story of Science, essentially promoting a counter-narrative to the Enlightenment Story of Science through articulating how humanity participates in an evolving universal consciousness through our embodied interaction and cooperative interdependence within nested, self-producing (autopoetic) systems, from the micro- to the macroscopic. This contemporary account of the natural world, its inter-related systems, and their dynamics may be understood as expressing a creative and generative energy—a kind of consciousness-that transcends the human yet also encompasses it

Cloud-based Meta-analysis to Bridge Science and Practice: Welcome to metaBUS

Although volumes have been written on spanning the science-practice gap in applied psychology, surprisingly few tangible components of that bridge have actually been constructed. We describe the metaBUS platform that addresses three challenges of one gap contributor: information overload. In particular, we describe challenges stemming from: (1) lack of access to research findings, (2) lack of an organizing map of topics studied, and (3) lack of interpretation guidelines for research findings. For each challenge, we show how metaBUS, which provides an advanced search and synthesis engine of currently more than 780,000 findings from 9,000 studies, can provide the building blocks needed to move beyond engineering design phase and toward construction, generating rapid, first-pass meta-analyses on virtually any topic to inform both research and practice. We provide an Internet link to access a preliminary version of the metaBUS interface and provide two brief demonstrations illustrating its functionality

Innovation dialogue - Being strategic in the face of complexity - Conference report

The Innovation Dialogue on Being Strategic in the Face of Complexity was held in Wageningen on 31 November and 1 December 2009. The event is part of a growing dialogue in the international development sector about the complexities of social, economic and political change. It builds on two previous events hosted the Innovation Dialogue on Navigating Complexity (May 2009) and the Seminar on Institutions, Theories of Change and Capacity Development (December 2008). Over 120 people attended the event coming from a range of Dutch and international development organizations. The event was aimed at bridging practitioner, policy and academic interests. It brought together people working on sustainable business strategies, social entrepreneurship and international development. Leading thinkers and practitioners offered their insights on what it means to "be strategic in complex times". The Dialogue was organized and hosted by the Wageningen UR Centre for Development Innovation working with the Chair Groups of Communication & Innovation Studies, Disaster Studies, Education & Competence Studies and Public Administration & Policy as co; organisers. The theme of the Dialogue aligns closely with Wageningen UR’s interest in linking technological and institutional innovation in ways that enable ‘science for impact’

Botnet Detection Using Graph Based Feature Clustering

Detecting botnets in a network is crucial because bot-activities impact numerous areas such as security, finance, health care, and law enforcement. Most existing rule and flow-based detection methods may not be capable of detecting bot-activities in an efficient manner. Hence, designing a robust botnet-detection method is of high significance. In this study, we propose a botnet-detection methodology based on graph-based features. Self-Organizing Map is applied to establish the clusters of nodes in the network based on these features. Our method is capable of isolating bots in small clusters while containing most normal nodes in the big-clusters. A filtering procedure is also developed to further enhance the algorithm efficiency by removing inactive nodes from bot detection. The methodology is verified using real-world CTU-13 and ISCX botnet datasets and benchmarked against classification-based detection methods. The results show that our proposed method can efficiently detect the bots despite their varying behaviors

From insights to innovations : data mining, visualization, and user interfaces

This thesis is about data mining (DM) and visualization methods for gaining insight into multidimensional data. Novel, exploratory data analysis tools and adaptive user interfaces are developed by tailoring and combining existing DM and visualization methods in order to advance in different applications. The thesis presents new visual data mining (VDM) methods that are also implemented in software toolboxes and applied to industrial and biomedical signals: First, we propose a method that has been applied to investigating industrial process data. The self-organizing map (SOM) is combined with scatterplots using the traditional color linking or interactive brushing. The original contribution is to apply color linked or brushed scatterplots and the SOM to visually survey local dependencies between a pair of attributes in different parts of the SOM. Clusters can be visualized on a SOM with different colors, and we also present how a color coding can be automatically obtained by using a proximity preserving projection of the SOM model vectors. Second, we present a new method for an (interactive) visualization of cluster structures in a SOM. By using a contraction model, the regular grid of a SOM visualization is smoothly changed toward a presentation that shows better the proximities in the data space. Third, we propose a novel VDM method for investigating the reliability of estimates resulting from a stochastic independent component analysis (ICA) algorithm. The method can be extended also to other problems of similar kind. As a benchmarking task, we rank independent components estimated on a biomedical data set recorded from the brain and gain a reasonable result. We also utilize DM and visualization for mobile-awareness and personalization. We explore how to infer information about the usage context from features that are derived from sensory signals. The signals originate from a mobile phone with on-board sensors for ambient physical conditions. In previous studies, the signals are transformed into descriptive (fuzzy or binary) context features. In this thesis, we present how the features can be transformed into higher-level patterns, contexts, by rather simple statistical methods: we propose and test using minimum-variance cost time series segmentation, ICA, and principal component analysis (PCA) for this purpose. Both time-series segmentation and PCA revealed meaningful contexts from the features in a visual data exploration. We also present a novel type of adaptive soft keyboard where the aim is to obtain an ergonomically better, more comfortable keyboard. The method starts from some conventional keypad layout, but it gradually shifts the keys into new positions according to the user's grasp and typing pattern. Related to the applications, we present two algorithms that can be used in a general context: First, we describe a binary mixing model for independent binary sources. The model resembles the ordinary ICA model, but the summation is replaced by the Boolean operator OR and the multiplication by AND. We propose a new, heuristic method for estimating the binary mixing matrix and analyze its performance experimentally. The method works for signals that are sparse enough. We also discuss differences on the results when using different objective functions in the FastICA estimation algorithm. Second, we propose "global iterative replacement" (GIR), a novel, greedy variant of a merge-split segmentation method. Its performance compares favorably to that of the traditional top-down binary split segmentation algorithm.reviewe

Visualizing and Interacting With Social Determinants of Health

Purpose: The purpose of this study is to examine the use of information visualization to represent specific social determinants of health, and to examine the benefits of such representation for health policymaking. Methods: The study developed a prototype for a visualization tool (www.healthvisualization.ca), which represents the conceptual framework for the social determinants of health (CSDH) and new ways to represent related health equity indicators. This tool was used by study participants. The experience of these participants and the usability of the tool were evaluated using qualitative semi-structured interviews. Results: Visualizing the CSDH framework helps to present the social determinants of health more effectively, allowing better visualization of indicators. Communicating healthcare indicators to policymakers is a complex task because of the complexity of these indicators. Conclusions: The contribution of information visualization to policymaking could only be understood by taking into consideration the different factors that impact health decision-making and evidence uptake

I-Light Symposium 2005 Proceedings

I-Light was made possible by a special appropriation by the State of Indiana. The research described at the I-Light Symposium has been supported by numerous grants from several sources. Any opinions, findings and conclusions, or recommendations expressed in the 2005 I-Light Symposium Proceedings are those of the researchers and authors and do not necessarily reflect the views of the granting agencies.Indiana University Office of the Vice President for Research and Information Technology, Purdue University Office of the Vice President for Information Technology and CI