Search (15 results, page 1 of 1)

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Content

"An einem trüben Novembertag 2008 sitzen zwei Männer an einem ovalen Konferenztisch. Sie befinden sich wie die meisten Geschäftstreibenden im Strudel der Finanzmärkte. Ihr Tisch steht im einzigen mehrstöckigen Nachwendebau der Berliner Karl-Marx-Allee. Links vom Fenster leuchtet die Spitze des Fernsehturms, rechts fällt der Blick auf kilometerlange Kachelfassaden. Die Verhandlungen mit den Investoren ziehen sich seit Wochen hin. Ein rhetorisches Ringen. Der Hirnforscher fragt: "Ist Wissen mit großem 'W' und wissen mit kleinem 'w' für Sie das Gleiche?" Der Vertriebsmann sagt: "Learntainment", "Knowledge Nuggets", "Mindmapping". Am Ende liegt ein unterschriebener Vertrag auf dem Tisch - an einem Tag, an dem Daimler laut über Kurzarbeit nachdenkt. Martin Hirsch und Ralf von Grafenstein genehmigen sich einen Piccolo. In der schwersten Wirtschaftskrise der Bundesrepublik haben sie für "eyePlorer" einen potenten Investor gefunden. Er hat die Tragweite ihrer Idee verstanden, und er hat begriffen: Die Welt ist eine Scheibe.
Eine neue visuelle Ordnung Martin Hirsch ist der Enkel des Nobelpreisträgers Werner Heisenberg. Außerdem ist er Hirnforscher und beschäftigt sich seit Jahren mit der Frage: Was tut mein Kopf eigentlich, während ich hirnforsche? Ralf von Grafenstein ist Marketingexperte und spezialisiert auf Dienstleistungen im Internet. Zusammen haben sie also am 1. Dezember 2008 eine Firma in Berlin gegründet, deren Heiliger Gral besagte Scheibe ist, auf der - das ist die Idee - bald die ganze Welt, die Internetwelt zumindest, Platz finden soll. Die Scheibe heißt eyePlorer, was sich als Aufforderung an ihre Nutzer versteht. Die sollen auf einer neuartigen, eben scheibenförmigen Plattform die unermesslichen Datensätze des Internets in eine neue visuelle Ordnung bringen. Der Schlüssel dafür, da waren sich Hirsch und von Grafenstein sicher, liegt in der Hirnforschung, denn warum nicht die assoziativen Fähigkeiten des Menschen auf Suchmaschinen übertragen? Anbieter wie Google lassen von solchen Ansätzen bislang die Finger. Hier setzt man dafür auf Volltextprogramme, also sprachbegabte Systeme, die letztlich aber, genau wie die Schlagwortsuche, nur zu opak gerankten Linksammlungen führen. Weiter als auf Seite zwei des Suchergebnisses wagt sich der träge Nutzer meistens nicht vor. Weil sie niemals wahrgenommen wird, fällt eine Menge möglicherweise kostbare Information unter den Tisch.
Skelett mit Sonnenbrille Hirsch sitzt in einem grell erleuchteten Konferenzraum. In der rechten Ecke steht ein Skelett, dem jemand eine Sonnenbrille aufgeklemmt hat. In der Hand hält Hirsch ein Modellgehirn, auf dem er im Rhythmus seines Sprachflusses mit den Fingern trommelt. Obwohl im Verlauf der nächsten Stunden erschreckend verwickelte Netzdiagramme zum Einsatz kommen, hält Hirsch sich an die Suggestivkraft des Bildes. Er sagt: "Das Primärerlebnis der Maschine ist bei Google das eines Jägers. Sie pirscht sich an eine Internetseite heran." Man denkt: "Genauso fühlt es sich an: Suchbegriff eingeben, 'enter' drücken, Website schießen!", schon kommt die Komplementärmetapher geschmeidig aus dem Köcher: Im Gegensatz zum Google-Jäger, sagt Hirsch, sei der eyePlorer ein Sammler, der stöbere, organisiere und dann von allem nasche. Hier werden Informationen, auf die handelsübliche Suchmaschinen nur verweisen, kulinarisch aufbereitet und zu Schwerpunkten verknüpft. Im Gegensatz zu ihren Vorgängern ist die Maschine ansatzweise intelligent. Sie findet im Laufe einer Sitzung heraus, worum es dem Benutzer geht, versteht den Zusammenhang von Suche und Inhalt und ist deshalb in der Lage, Empfehlungen auszusprechen.
Einstein, Weizsäcker und Hitler Zu Demonstrationszwecken wird die eyePlorer-Scheibe an die Wand projiziert. Gibt man im kleinen Suchfeld in der Mitte den Namen Werner Heisenberg ein, verwandelt sich die Scheibe in einen Tortenboden. Die einzelnen Stücke entsprechen Kategorien wie "Person", "Technologie" oder "Organisation". Sie selbst sind mit bunten Knöpfen bedeckt, unter denen sich die Informationen verbergen. So kommt es, dass man beim Thema Heisenberg nicht nur auf die Kollegen Einstein, Weizsäcker und Schrödinger trifft, sondern auch auf Adolf Hitler. Ein Klick auf den entsprechenden Button stellt unter anderem heraus: Heisenberg kam 1933 unter Beschuss der SS, weil er sich nicht vor den Karren einer antisemitischen Physikbewegung spannen ließ. Nach diesem Prinzip spült die frei assoziierende Maschine vollautomatisch immer wieder neue Fakten an, um die der Nutzer zwar nicht gebeten hat, die ihn bei seiner Recherche aber möglicherweise unterstützen und die er später - die Maschine ist noch ausbaubedürftig - auch modellieren darf. Aber will man das, sich von einer Maschine beraten lassen? "Google ist wie ein Zoo", sekundiert Ralf von Grafenstein. "In einem Gehege steht eine Giraffe, im anderen ein Raubtier, aber die sind klar getrennt voneinander durch Gitter und Wege. Es gibt keine Möglichkeit, sie zusammen anzuschauen. Da kommen wir ins Spiel. Wir können Äpfel mit Birnen vergleichen!" Die Welt ist eine Scheibe oder die Scheibe eben eine Welt, auf der vieles mit vielem zusammenhängt und manches auch mit nichts. Der Vorteil dieser Maschine ist, dass sie in Zukunft Sinn stiften könnte, wo andere nur spröde auf Quellen verweisen. "Google ist ja ein unheimlich heterogenes Erlebnis mit ständigen Wartezeiten und Mausklicks dazwischen. Das kostet mich viel zu viel Metagedankenkraft", sagt Hirsch. "Wir wollten eine Maschine mit einer ästhetisch ansprechenden Umgebung bauen, aus der ich mich kaum wegbewege, denn sie liefert mir Informationen in meinen Gedanken hinein."
Wenn die Maschine denkt Zur Hybris des Projekts passt, dass der eyePlorer ursprünglich HAL heißen sollte - wie der außer Rand und Band geratene Bordcomputer aus Kubricks "2001: Odyssee im Weltraum". Wenn man die Buchstaben aber jeweils um eine Alphabetposition nach rechts verrückt, ergibt sich IBM. Was passiert mit unserem Wissen, wenn die Maschine selbst anfängt zu denken? Ralf von Grafenstein macht ein ernstes Gesicht. "Es ist nicht unser Ansinnen, sie alleinzulassen. Es geht bei uns ja nicht nur darum, zu finden, sondern auch mitzumachen. Die Community ist wichtig. Der Dialog ist beiderseitig." Der Lotse soll in Form einer wachsamen Gemeinschaft also an Bord bleiben. Begünstigt wird diese Annahme auch durch die aufkommenden Anfasstechnologien, mit denen das iPhone derzeit so erfolgreich ist: "Allein zehn Prozent der menschlichen Gehirnleistung gehen auf den Pinzettengriff zurück." Martin Hirsch wundert sich, dass diese Erkenntnis von der IT-Branche erst jetzt berücksichtigt wird. Auf berührungssensiblen Bildschirmen sollen die Nutzer mit wenigen Handgriffen bald spielerisch Inhalte schaffen und dem System zur Verfügung stellen. So wird aus der Suchmaschine ein "Sparringspartner" und aus einem Informationsknopf ein "Knowledge Nugget". Wie auch immer man die Erkenntniszutaten des Internetgroßmarkts serviert: Wissen als Zeitwort ist ein länglicher Prozess. Im Moment sei die Maschine noch auf dem Stand eines Zweijährigen, sagen ihre Schöpfer. Sozialisiert werden soll sie demnächst im Internet, ihre Erziehung erfolgt dann durch die Nutzer. Als er Martin Hirsch mit seiner Scheibe zum ersten Mal gesehen habe, dachte Ralf von Grafenstein: "Das ist überfällig! Das wird kommen! Das muss raus!" Jetzt ist es da, klein, unschuldig und unscheinbar. Man findet es bei Google."

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Abstract

QVIZ will research and create a framework for visualizing and querying archival resources by a time-space interface based on maps and emergent knowledge structures. The framework will also integrate social software, such as wikis, in order to utilize knowledge in existing and new communities of practice. QVIZ will lead to improved information sharing and knowledge creation, easier access to information in a user-adapted context and innovative ways of exploring and visualizing materials over time, between countries and other administrative units. The common European framework for sharing and accessing archival information provided by the QVIZ project will open a considerably larger commercial market based on archival materials as well as a richer understanding of European history.

Content

Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

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Abstract

Diese Diplomarbeit beschäftigt sich mit der Erstellung eines PlugIns für den Ontologie-Editor Protégé. Das PlugIn visualisiert Objekt-Properties als Verknüpfungen zwischen zwei OWL-Klassen. Als Ausgangspunkt für die Entwicklung dient das PlugIn OWLViz, das Vererbungshierarchien von OWL-Klassen als Graphen darstellt. Die Platzierung der Knoten und Kanten des Graphen wird von Algorithmen der Programmbibliothek Graphviz vorgenommen.

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Abstract

Das WWW entwickelte sich aus dem Bedürfnis, textuelle Information einfach und schnell zu durchforsten. Dabei entstand das Konzept des 'Hyperlinks', womit es möglich ist, Texte miteinander zu verknüpfen. Die Anzahl der Webseiten nahm mit der Verbreitung des WWW rapide zu. Das Problem heutzutage ist: Es gibt prinzipiell jede Art von Information im Internet, doch wie kommt man da dran?

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Abstract

The paper presents a new unsupervised dimensionality reduction technique, called parametric t-SNE, that learns a parametric mapping between the high-dimensional data space and the low-dimensional latent space. Parametric t-SNE learns the parametric mapping in such a way that the local structure of the data is preserved as well as possible in the latent space. We evaluate the performance of parametric t-SNE in experiments on three datasets, in which we compare it to the performance of two other unsupervised parametric dimensionality reduction techniques. The results of experiments illustrate the strong performance of parametric t-SNE, in particular, in learning settings in which the dimensionality of the latent space is relatively low.

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Abstract

Interface designs for lexical databases in NLP have suffered from not following design principles developed in the information visualization research community. We present a design paradigm and show it can be used to generate visualizations which maximize the usability and utility ofWordNet. The techniques can be generally applied to other lexical databases used in NLP research.

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Abstract

This paper aims to identify what information visualisation is and how in conjunction with the computer it can be used as a tool to expand understanding. It also seeks to explain how information visualisation has been fundamental to the development of the computer from its very early days to Apple's launch of the now ubiquitous W.I.M.P (Windows, Icon, Menu, Program) graphical user interface in 1984. An attempt is also made to question why after many years of progress and development though the late 1960s and 1970s, very little has changed in the way we interact with the data on our computers since the watershed of the Macintosh and in conclusion where the future of information visualisation may lie.

Content

Dissertation for MA degree in electronic media, School of Humanities, Oxford Brookes University

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Abstract

A visual thesaurus system and method for displaying a selected term in association with its one or more meanings, other words to which it is related, and further relationship information. The results of a search are presented in a directed graph that provides more information than an ordered list. When a user selects one of the results, the display reorganizes around the user's search allowing for further searches, without the interruption of going to additional pages.

Content

Traditional print reference guides often have two methods of finding information: an order (alphabetical for dictionaries and encyclopedias, by subject hierarchy in the case of thesauri) and indices (ordered lists, with a more complete listing of words and concepts, which refers back to original content from the main body of the book). A user of such traditional print reference guides who is looking for information will either browse through the ordered information in the main body of the reference book, or scan through the indices to find what is necessary. The advent of the computer allows for much more rapid electronic searches of the same information, and for multiple layers of indices. Users can either search through information by entering a keyword, or users can browse through the information through an outline index, which represents the information contained in the main body of the data. There are two traditional user interfaces for such applications. First, the user may type text into a search field and in response, a list of results is returned to the user. The user then selects a returned entry and may page through the resulting information. Alternatively, the user may choose from a list of words from an index. For example, software thesaurus applications, in which a user attempts to find synonyms, antonyms, homonyms, etc. for a selected word, are usually implemented using the conventional search and presentation techniques discussed above. The presentation of results only allows for a one-dimensional order of data at any one time. In addition, only a limited number of results can be shown at once, and selecting a result inevitably leads to another page-if the result is not satisfactory, the users must search again. Finally, it is difficult to present information about the manner in which the search results are related, or to present quantitative information about the results without causing confusion. Therefore, there exists a need for a multidimensional graphical display of information, in particular with respect to information relating to the meaning of words and their relationships to other words. There further exists a need to present large amounts of information in a way that can be manipulated by the user, without the user losing his place. And there exists a need for more fluid, intuitive and powerful thesaurus functionality that invites the exploration of language.

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Abstract

The concept of c-space is proposed as a visualization schema relating containers of content to cataloging surrogates and classification structures. Possible applications of keyword vector clusters within c-space could include improved retrieval rates through the use of captioning within visual hierarchies, tracings of semantic bleeding among subclasses, and access to buried knowledge within subject-neutral publication containers. The Scholastica Project is described as one example, following a tradition of research dating back to the 1980's. Preliminary focus group assessment indicates that this type of classification rendering may offer digital library searchers enriched entry strategies and an expanded range of re-entry vocabularies. Those of us who work in traditional libraries typically assume that our systems of classification: Library of Congress Classification (LCC) and Dewey Decimal Classification (DDC), are descriptive rather than prescriptive. In other words, LCC classes and subclasses approximate natural groupings of texts that reflect an underlying order of knowledge, rather than arbitrary categories prescribed by librarians to facilitate efficient shelving. Philosophical support for this assumption has traditionally been found in a number of places, from the archetypal tree of knowledge, to Aristotelian categories, to the concept of discursive formations proposed by Michel Foucault. Gary P. Radford has elegantly described an encounter with Foucault's discursive formations in the traditional library setting: "Just by looking at the titles on the spines, you can see how the books cluster together...You can identify those books that seem to form the heart of the discursive formation and those books that reside on the margins. Moving along the shelves, you see those books that tend to bleed over into other classifications and that straddle multiple discursive formations. You can physically and sensually experience...those points that feel like state borders or national boundaries, those points where one subject ends and another begins, or those magical places where one subject has morphed into another..."
But what happens to this awareness in a digital library? Can discursive formations be represented in cyberspace, perhaps through diagrams in a visualization interface? And would such a schema be helpful to a digital library user? To approach this question, it is worth taking a moment to reconsider what Radford is looking at. First, he looks at titles to see how the books cluster. To illustrate, I scanned one hundred books on the shelves of a college library under subclass HT 101-395, defined by the LCC subclass caption as Urban groups. The City. Urban sociology. Of the first 100 titles in this sequence, fifty included the word "urban" or variants (e.g. "urbanization"). Another thirty-five used the word "city" or variants. These keywords appear to mark their titles as the heart of this discursive formation. The scattering of titles not using "urban" or "city" used related terms such as "town," "community," or in one case "skyscrapers." So we immediately see some empirical correlation between keywords and classification. But we also see a problem with the commonly used search technique of title-keyword. A student interested in urban studies will want to know about this entire subclass, and may wish to browse every title available therein. A title-keyword search on "urban" will retrieve only half of the titles, while a search on "city" will retrieve just over a third. There will be no overlap, since no titles in this sample contain both words. The only place where both words appear in a common string is in the LCC subclass caption, but captions are not typically indexed in library Online Public Access Catalogs (OPACs). In a traditional library, this problem is mitigated when the student goes to the shelf looking for any one of the books and suddenly discovers a much wider selection than the keyword search had led him to expect. But in a digital library, the issue of non-retrieval can be more problematic, as studies have indicated. Micco and Popp reported that, in a study funded partly by the U.S. Department of Education, 65 of 73 unskilled users searching for material on U.S./Soviet foreign relations found some material but never realized they had missed a large percentage of what was in the database.

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Abstract

This is a preprint to be published in the Extensions & Corrections to the UDC. The paper explains the basic functions of browsing and searching that need to be supported in relation to analytico-synthetic classifications such as Universal Decimal Classification (UDC), irrespective of any specific, real-life implementation. UDC is an example of a semi-faceted system that can be used, for instance, for both post-coordinate searching and hierarchical/facet browsing. The advantages of using a classification for IR, however, depend on the strength of the GUI, which should provide a user-friendly interface to classification browsing and searching. The power of this interface is in supporting visualisation that will 'convert' what is potentially a user-unfriendly indexing language based on symbols, to a subject presentation that is easy to understand, search and navigate. A summary of the basic functions of searching and browsing a classification that may be provided on a user-friendly interface is given and examples of classification browsing interfaces are provided.

Content

To be published in the Extensions & Corrections to the UDC. 28(2006).

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Abstract

In this article we present a method for retrieving documents from a digital library through a visual interface based on automatically generated concepts. We used a vocabulary generation algorithm to generate a set of concepts for the digital library and a technique called the max-min distance technique to cluster them. Additionally, the concepts were visualized in a spring embedding graph layout to depict the semantic relationship among them. The resulting graph layout serves as an aid to users for retrieving documents. An online archive containing the contents of D-Lib Magazine from July 1995 to May 2002 was used to test the utility of an implemented retrieval and visualization system. We believe that the method developed and tested can be applied to many different domains to help users get a better understanding of online document collections and to minimize users' cognitive load during execution of search tasks. Over the past few years, the volume of information available through the World Wide Web has been expanding exponentially. Never has so much information been so readily available and shared among so many people. Unfortunately, the unstructured nature and huge volume of information accessible over networks have made it hard for users to sift through and find relevant information. To deal with this problem, information retrieval (IR) techniques have gained more intensive attention from both industrial and academic researchers. Numerous IR techniques have been developed to help deal with the information overload problem. These techniques concentrate on mathematical models and algorithms for retrieval. Popular IR models such as the Boolean model, the vector-space model, the probabilistic model and their variants are well established.
From the user's perspective, however, it is still difficult to use current information retrieval systems. Users frequently have problems expressing their information needs and translating those needs into queries. This is partly due to the fact that information needs cannot be expressed appropriately in systems terms. It is not unusual for users to input search terms that are different from the index terms information systems use. Various methods have been proposed to help users choose search terms and articulate queries. One widely used approach is to incorporate into the information system a thesaurus-like component that represents both the important concepts in a particular subject area and the semantic relationships among those concepts. Unfortunately, the development and use of thesauri is not without its own problems. The thesaurus employed in a specific information system has often been developed for a general subject area and needs significant enhancement to be tailored to the information system where it is to be used. This thesaurus development process, if done manually, is both time consuming and labor intensive. Usage of a thesaurus in searching is complex and may raise barriers for the user. For illustration purposes, let us consider two scenarios of thesaurus usage. In the first scenario the user inputs a search term and the thesaurus then displays a matching set of related terms. Without an overview of the thesaurus - and without the ability to see the matching terms in the context of other terms - it may be difficult to assess the quality of the related terms in order to select the correct term. In the second scenario the user browses the whole thesaurus, which is organized as in an alphabetically ordered list. The problem with this approach is that the list may be long, and neither does it show users the global semantic relationship among all the listed terms.
Nevertheless, because thesaurus use has shown to improve retrieval, for our method we integrate functions in the search interface that permit users to explore built-in search vocabularies to improve retrieval from digital libraries. Our method automatically generates the terms and their semantic relationships representing relevant topics covered in a digital library. We call these generated terms the "concepts", and the generated terms and their semantic relationships we call the "concept space". Additionally, we used a visualization technique to display the concept space and allow users to interact with this space. The automatically generated term set is considered to be more representative of subject area in a corpus than an "externally" imposed thesaurus, and our method has the potential of saving a significant amount of time and labor for those who have been manually creating thesauri as well. Information visualization is an emerging discipline and developed very quickly in the last decade. With growing volumes of documents and associated complexities, information visualization has become increasingly important. Researchers have found information visualization to be an effective way to use and understand information while minimizing a user's cognitive load. Our work was based on an algorithmic approach of concept discovery and association. Concepts are discovered using an algorithm based on an automated thesaurus generation procedure. Subsequently, similarities among terms are computed using the cosine measure, and the associations among terms are established using a method known as max-min distance clustering. The concept space is then visualized in a spring embedding graph, which roughly shows the semantic relationships among concepts in a 2-D visual representation. The semantic space of the visualization is used as a medium for users to retrieve the desired documents. In the remainder of this article, we present our algorithmic approach of concept generation and clustering, followed by description of the visualization technique and interactive interface. The paper ends with key conclusions and discussions on future work.

Theme

Semantisches Umfeld in Indexierung u. Retrieval

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Abstract

User interfaces for digital information discovery often require users to click around and read a lot of text in order to find the text they want to read-a process that is often frustrating and tedious. This is exacerbated because of the limited amount of text that can be displayed on a computer screen. To improve the user experience of computer mediated information discovery, information visualization techniques are applied to the digital library context, while retaining traditional information organization concepts. In this article, the "virtual (book) spine" and the virtual spine viewer are introduced. The virtual spine viewer is an application which allows users to visually explore large information spaces or collections while also allowing users to hone in on individual resources of interest. The virtual spine viewer introduced here is an alpha prototype, presented to promote discussion and further work. Information discovery changed radically with the introduction of computerized library access catalogs, the World Wide Web and its search engines, and online bookstores. Yet few instances of these technologies provide a user experience analogous to walking among well-organized, well-stocked bookshelves-which many people find useful as well as pleasurable. To put it another way, many of us have heard or voiced complaints about the paucity of "online browsing"-but what does this really mean? In traditional information spaces such as libraries, often we can move freely among the books and other resources. When we walk among organized, labeled bookshelves, we get a sense of the information space-we take in clues, perhaps unconsciously, as to the scope of the collection, the currency of resources, the frequency of their use, etc. We also enjoy unexpected discoveries such as finding an interesting resource because library staff deliberately located it near similar resources, or because it was miss-shelved, or because we saw it on a bookshelf on the way to the water fountain.
When our experience of information discovery is mediated by a computer, we neither move ourselves nor the monitor. We have only the computer's monitor to view, and the keyboard and/or mouse to manipulate what is displayed there. Computer interfaces often reduce our ability to get a sense of the contents of a library: we don't perceive the scope of the library: its breadth, (the quantity of materials/information), its density (how full the shelves are, how thorough the collection is for individual topics), or the general audience for the materials (e.g., whether the materials are appropriate for middle school students, college professors, etc.). Additionally, many computer interfaces for information discovery require users to scroll through long lists, to click numerous navigational links and to read a lot of text to find the exact text they want to read. Text features of resources are almost always presented alphabetically, and the number of items in these alphabetical lists sometimes can be very long. Alphabetical ordering is certainly an improvement over no ordering, but it generally has no bearing on features with an inherent non-alphabetical ordering (e.g., dates of historical events), nor does it necessarily group similar items together. Alphabetical ordering of resources is analogous to one of the most familiar complaints about dictionaries: sometimes you need to know how to spell a word in order to look up its correct spelling in the dictionary. Some have used technology to replicate the appearance of physical libraries, presenting rooms of bookcases and shelves of book spines in virtual 3D environments. This approach presents a problem, as few book spines can be displayed legibly on a monitor screen. This article examines the role of book spines, call numbers, and other traditional organizational and information discovery concepts, and integrates this knowledge with information visualization techniques to show how computers and monitors can meet or exceed similar information discovery methods. The goal is to tap the unique potentials of current information visualization approaches in order to improve information discovery, offer new services, and most important of all, improve user satisfaction. We need to capitalize on what computers do well while bearing in mind their limitations. The intent is to design GUIs to optimize utility and provide a positive experience for the user.

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Abstract

UDC aims to be a consistent and complete classification system, that enables practitioners to classify documents swiftly and smoothly. The eventual goal of UDC is to enable the public at large to retrieve documents from large collections of documents that are classified with UDC. The large size of the UDC Master Reference File, MRF with over 66.000 records, makes it difficult to obtain an overview and to understand its structure. Moreover, finding the right classification in MRF turns out to be difficult in practice. Last but not least, retrieval of documents requires insight and understanding of the coding system. Visualization is an effective means to support the development of UDC as well as its use by practitioners. Moreover, visualization offers possibilities to use the classification without use of the coding system as such. MagnaView has developed an application which demonstrates the use of interactive visualization to face these challenges. In our presentation, we discuss these challenges, and we give a demonstration of the way the application helps face these. Examples of visualizations can be found below.

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Abstract

We present a new technique called "t-SNE" that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map. The technique is a variation of Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map. t-SNE is better than existing techniques at creating a single map that reveals structure at many different scales. This is particularly important for high-dimensional data that lie on several different, but related, low-dimensional manifolds, such as images of objects from multiple classes seen from multiple viewpoints. For visualizing the structure of very large data sets, we show how t-SNE can use random walks on neighborhood graphs to allow the implicit structure of all of the data to influence the way in which a subset of the data is displayed. We illustrate the performance of t-SNE on a wide variety of data sets and compare it with many other non-parametric visualization techniques, including Sammon mapping, Isomap, and Locally Linear Embedding. The visualizations produced by t-SNE are significantly better than those produced by the other techniques on almost all of the data sets.

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Abstract

Many real-world domains can be represented as large node-link graphs: backbone Internet routers connect with 70,000 other hosts, mid-sized Web servers handle between 20,000 and 200,000 hyperlinked documents, and dictionaries contain millions of words defined in terms of each other. Computational manipulation of such large graphs is common, but previous tools for graph visualization have been limited to datasets of a few thousand nodes. Visual depictions of graphs and networks are external representations that exploit human visual processing to reduce the cognitive load of many tasks that require understanding of global or local structure. We assert that the two key advantages of computer-based systems for information visualization over traditional paper-based visual exposition are interactivity and scalability. We also argue that designing visualization software by taking the characteristics of a target user's task domain into account leads to systems that are more effective and scale to larger datasets than previous work. This thesis contains a detailed analysis of three specialized systems for the interactive exploration of large graphs, relating the intended tasks to the spatial layout and visual encoding choices. We present two novel algorithms for specialized layout and drawing that use quite different visual metaphors. The H3 system for visualizing the hyperlink structures of web sites scales to datasets of over 100,000 nodes by using a carefully chosen spanning tree as the layout backbone, 3D hyperbolic geometry for a Focus+Context view, and provides a fluid interactive experience through guaranteed frame rate drawing. The Constellation system features a highly specialized 2D layout intended to spatially encode domain-specific information for computational linguists checking the plausibility of a large semantic network created from dictionaries. The Planet Multicast system for displaying the tunnel topology of the Internet's multicast backbone provides a literal 3D geographic layout of arcs on a globe to help MBone maintainers find misconfigured long-distance tunnels. Each of these three systems provides a very different view of the graph structure, and we evaluate their efficacy for the intended task. We generalize these findings in our analysis of the importance of interactivity and specialization for graph visualization systems that are effective and scalable.