Search (51 results, page 1 of 3)

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Abstract

Grounded on real industrial use cases, we recently proposed an ontology-based visual query system for SPARQL, named OptiqueVQS. Ontology-based visual query systems employ ontologies and visual representations to depict the domain of interest and queries, and are promising to enable end users without any technical background to access data on their own. However, even with considerably small ontologies, the number of ontology elements to choose from increases drastically, and hence hinders usability. Therefore, in this paper, we propose a method using the log of past queries for ranking and suggesting query extensions as a user types a query, and identify emerging issues to be addressed.

Source

Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al

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Abstract

Das Screen-Design-Handbuch gibt Gestaltern interaktiver Medien eine praktische Arbeitshilfe an die Hand, um Informationen zielgruppen- und mediengerecht aufzubereiten und darzustellen. Es zeigt Hintergründe und Zusammenhänge auf, verdeutlicht diese anhand von Beispielen und regt dazu an, die Sprache der digitalen Medien weiter zu entwickeln. Grundlagen der Wahrnehmungs- und Lernpsychologie, der Ergonomie, der Kommunikationstheorie, der Imagery-Forschung und der Ästhethik werden dabei ebenso berücksichtigt wie Fragen der Gestaltung von Navigations- und Orientierungselementen. Die Neuauflage enthält mehr Beispiele und Checklisten sowie neue Kapitel über Wahrnehmung, Web-Nutzung und Projektmanagement

Date

22. 3.2008 14:35:21

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Abstract

The idea of constructing science maps based on bibliographic data has intrigued researchers for decades, and various techniques have been developed to map the structure of research disciplines. Most science mapping studies use a single method. However, as research fields have various properties, a valid map of a field should actually be composed of a set of maps derived from a series of investigations using different methods. That leads to the question of what can be learned from a combination-triangulation-of these different science maps. In this paper we propose a method for triangulation, using the example of water science. We combine three different mapping approaches: journal-journal citation relations (JJCR), shared author keywords (SAK), and title word-cited reference co-occurrence (TWRC). Our results demonstrate that triangulation of JJCR, SAK, and TWRC produces a more comprehensive picture than each method applied individually. The outcomes from the three different approaches can be associated with each other and systematically interpreted to provide insights into the complex multidisciplinary structure of the field of water research.

Date

16.11.2017 13:29:12

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Abstract

Zweidimensionale Karten dienen im Information Retrieval (IR) immer häufiger der Visualisierung von Dokumentbeständen. Über die Qualität der verschiedenen Methoden zur Erzeugung dieser Karten ist wenig bekannt. In diesem Artikel werden nach einem Überblick über Stand der Forschung und Technik zu Visualisierungen und ihrer Bewertung zwei Verfahren hinsichtlich ihrer Unterschiede verglichen. Die Evaluierung basiert auf der Perspektive des Benutzers beim Browsing in einer Karte. Das Experiment zeigt, dass die Methoden sowohl bei großen als auch bei kleinen Dokumentenmengen zu sehr unterschiedlichen Karten führen und zwischen den Karten keine Korrelation besteht. Das Ergebnis der Untersuchung ist in zweifacher Hinsicht interpretierbar. zum einen kann nicht davon ausgegangen werden, dass sich ein spezielles Verfahren der Dimensionsreduktion eindeutig anbietet, es muss also auf den speziellen Anwendungsfall hin überprüft werden, welches Verfahren anzuwenden ist. Zum anderen scheint aber auch kein Verfahren zu vollkommen unbrauchbaren Ergebnissen zu führen, so dass davon ausgegangen werden kann, dass die einzelnen Verfahren einander ergänzend unterschiedliche Aspekte des Dokumentbestandes beleuchten. Hierzu sollten weitere Tests folgen.

Date

29. 1.2005 19:17:50

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Abstract

Findings - The results indicate that both WikiMap and WNavis supported users to identify concepts and their relations better compared to the baseline. In topical tasks WNavis over performed both WikiMap and the baseline system. Although there were no time differences in finding concepts or answering topical questions, the test systems provided users with a greater gain per time unit. The users of WNavis leaned on the hierarchy tree instead of other tools, whereas WikiMap users used the topic map. Research limitations/implications - The findings have implications for the design of IR support tools in knowledge-intensive web sites that help users to explore topics and concepts. Originality/value - The authors explored to what extent the use of each IV support tool contributed to successful exploration of topics in search tasks. The authors propose extended task-based evaluation measures to understand how each application provides useful context for users to accomplish the tasks and attain the search goals. That is, the authors not only evaluate the output of the search results, e.g. the number of relevant items retrieved, but also the outcome provided by the system for assisting users to attain the search goal.

Date

8. 4.2015 16:20:29

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BK

70.03 Methoden, Techniken und Organisation der sozialwissenschaftlichen Forschung

Classification

70.03 Methoden, Techniken und Organisation der sozialwissenschaftlichen Forschung

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Abstract

Map-based visualizations of document collections have become popular in recent times. However, most of these visualizations emphasize only geospatial properties of objects, leaving out other ontological properties. In this paper we propose to extend these visualizations to include nongeospatial properties of documents to support users with elementary and synoptic visual tasks. More specifically, additional suitable representations that can enhance the utility of map-based visualizations are discussed. To demonstrate the utility of the proposed solution, we have developed a prototype map-based visualization system using Google Maps (GM), which demonstrates how additional representations can be beneficial.

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Abstract

We propose an approach to visualizing the scientific world and its evolution by constructing minimum spanning trees (MSTs) and a two-dimensional map of scientific journals using the database of the Science Citation Index (SCI) during 1994-2001. The structures of constructed MSTs are consistent with the sorting of SCI categories. The map of science is constructed based on our MST results. Such a map shows the relation among various knowledge clusters and their citation properties. The temporal evolution of the scientific world can also be delineated in the map. In particular, this map clearly shows a linear structure of the scientific world, which contains three major domains including physical sciences, life sciences, and medical sciences. The interaction of various knowledge fields can be clearly seen from this scientific world map. This approach can be applied to various levels of knowledge domains.

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Abstract

In this article, we propose a graph-based interactive bibliographic information retrieval system-GIBIR. GIBIR provides an effective way to retrieve bibliographic information. The system represents bibliographic information as networks and provides a form-based query interface. Users can develop their queries interactively by referencing the system-generated graph queries. Complex queries such as "papers on information retrieval, which were cited by John's papers that had been presented in SIGIR" can be effectively answered by the system. We evaluate the proposed system by developing another relational database-based bibliographic information retrieval system with the same interface and functions. Experiment results show that the proposed system executes the same queries much faster than the relational database-based system, and on average, our system reduced the execution time by 72% (for 3-node query), 89% (for 4-node query), and 99% (for 5-node query).

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Abstract

The use of thesaurus-based indexing is a common approach for increasing the performance of information retrieval. In this thesis, we examine the suitability of a thesaurus for a given set of information and evaluate improvements of existing thesauri to get better search results. On this area, we focus on two aspects: 1. We demonstrate an analysis of the indexing results achieved by an automatic document indexer and the involved thesaurus. 2. We propose a method for thesaurus evaluation which is based on a combination of statistical measures and appropriate visualization techniques that support the detection of potential problems in a thesaurus. In this chapter, we give an overview of the context of our work. Next, we briefly outline the basics of thesaurus-based information retrieval and describe the Collexis Engine that was used for our experiments. In Chapter 3, we describe two experiments in automatically indexing documents in the areas of medicine and economics with corresponding thesauri and compare the results to available manual annotations. Chapter 4 describes methods for assessing thesauri and visualizing the result in terms of a treemap. We depict examples of interesting observations supported by the method and show that we actually find critical problems. We conclude with a discussion of open questions and future research in Chapter 5.

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Abstract

In this article and two other articles which conceptualize a future stage of the research program (Leide, Cole, Large, & Beheshti, submitted for publication; Cole, Leide, Large, Beheshti, & Brooks, in preparation), we map-out a domain novice user's encounter with an IR system from beginning to end so that appropriate classification-based visualization schemes can be inserted into the encounter process. This article describes the visualization of a navigation classification scheme only. The navigation classification scheme uses the metaphor of a ship and ship's navigator traveling through charted (but unknown to the user) waters, guided by a series of lighthouses. The lighthouses contain mediation interfaces linking the user to the information store through agents created for each. The user's agent is the cognitive model the user has of the information space, which the system encourages to evolve via interaction with the system's agent. The system's agent is an evolving classification scheme created by professional indexers to represent the structure of the information store. We propose a more systematic, multidimensional approach to creating evolving classification/indexing schemes, based on where the user is and what she is trying to do at that moment during the search session.

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Abstract

Visitors to museums and other cultural heritage sites encounter a wealth of exhibits in a variety of subject areas, but can explore only a small number of them. Moreover, there typically exists rich complementary information that can be delivered to the visitor about exhibits of interest, but only a fraction of this information can be consumed during the limited time of the visit. Recommender systems may help visitors to cope with this information overload. Ideally, the recommender system of choice should model user preferences, as well as background knowledge about the museum's environment, considering aspects of physical and thematic relevancy. We propose a personalized graph-based recommender framework, representing rating history and background multi-facet information jointly as a relational graph. A random walk measure is applied to rank available complementary multimedia presentations by their relevancy to a visitor's profile, integrating the various dimensions. We report the results of experiments conducted using authentic data collected at the Hecht museum. An evaluation of multiple graph variants, compared with several popular and state-of-the-art recommendation methods, indicates on advantages of the graph-based approach.

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Abstract

Recent efforts in biomedical visual question answering (VQA) research rely on combined information gathered from the image content and surrounding text supporting the figure. Biomedical journals are a rich source of information for such multimodal content indexing. For multipanel figures in these journals, it is critical to develop automatic figure panel splitting and label recognition algorithms to associate individual panels with text metadata in the figure caption and the body of the article. Challenges in this task include large variations in figure panel layout, label location, size, contrast to background, and so on. In this work, we propose a deep convolutional neural network, which splits the panels and recognizes the panel labels in a single step. Visual features are extracted from several layers at various depths of the backbone neural network and organized to form a feature pyramid. These features are fed into classification and regression networks to generate candidates of panels and their labels. These candidates are merged to create the final panel segmentation result through a beam search algorithm. We evaluated the proposed algorithm on the ImageCLEF data set and achieved better performance than the results reported in the literature. In order to thoroughly investigate the proposed algorithm, we also collected and annotated our own data set of 10,642 figures. The experiments, trained on 9,642 figures and evaluated on the remaining 1,000 figures, show that combining panel splitting and panel label recognition mutually benefit each other.

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Abstract

Die Wissenschaft befindet sich in einer Auffindbarkeitskrise. Obwohl durch die Open Access-Bewegung Forschungsergebnisse besser zugänglich geworden sind, wird ein signifikanter Teil der Outputs nicht nachgenutzt. Einen großen Anteil an der Krise haben die Tools, die für die Literatursuche verwendet werden. Angesichts von drei Millionen Veröffentlichungen pro Jahr sind klassische Ansätze, wie etwa listenbasierte Suchmaschinen, nicht mehr ausreichend. Open Knowledge Maps hat es sich zum Ziel gesetzt, die Auffindbarkeit wissenschaftlichen Wissens zu verbessern. Dafür betreibt die gemeinnützige Organisation aus Österreich die weltweit größte visuelle Suchmaschine für Forschung. Das Grundprinzip besteht darin, Wissenslandkarten für die Literatursuche zu nutzen. Diese geben einen Überblick über ein Forschungsfeld und ermöglichen so einen schnelleren Einstieg in die Literatur. Open Knowledge Maps basiert auf den Prinzipien von Open Science: Inhalte, Daten und Software werden unter einer freien Lizenz veröffentlicht. Dadurch entsteht eine offene, wiederverwendbare Infrastruktur; Lock-In-Effekte, wie sie bei proprietären Systemen auftreten, werden vermieden. Open Knowledge Maps arbeitet seit Beginn eng mit Bibliotheken und BibliothekarInnen als ExpertInnen für Wissensorganisation und -verwaltung zusammen. Im Rahmen eines konsortialen Fördermodells werden Bibliotheken nun eingeladen, das System stärker mitzugestalten - unter anderem bei wichtigen Zukunftsthemen wie der besseren Auffindbarkeit von Datensätzen.

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Abstract

In the last few years, there is an increasing interest to generate visual representations of very large scientific domains. A methodology based on the combined use of ISI-JCR category cocitation and social networks analysis through the use of the Pathfinder algorithm has demonstrated its ability to achieve high quality, schematic visualizations for these kinds of domains. Now, the next step would be to generate these scientograms in an on-line fashion. To do so, there is a need to significantly decrease the run time of the latter pruning technique when working with category cocitation matrices of a large dimension like the ones handled in these large domains (Pathfinder has a time complexity order of O(n4), with n being the number of categories in the cocitation matrix, i.e., the number of nodes in the network). Although a previous improvement called Binary Pathfinder has already been proposed to speed up the original algorithm, its significant time complexity reduction is not enough for that aim. In this paper, we make use of a different shortest path computation from classical approaches in computer science graph theory to propose a new variant of the Pathfinder algorithm which allows us to reduce its time complexity in one order of magnitude, O(n3), and thus to significantly decrease the run time of the implementation when applied to large scientific domains considering the parameter q = n - 1. Besides, the new algorithm has a much simpler structure than the Binary Pathfinder as well as it saves a significant amount of memory with respect to the original Pathfinder by reducing the space complexity to the need of just storing two matrices. An experimental comparison will be developed using large networks from real-world domains to show the good performance of the new proposal.

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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".

Date

20. 1.2008 17:28:29

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Date

22. 3.2008 14:29:25

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Date

5. 8.2006 10:16:29