Search (38 results, page 1 of 2)

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Abstract

This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.

Date

22. 7.2006 16:11:05

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Abstract

Generally, Computer Science (CS) classifications are inconsistent in taxonomy strategies. t is necessary to develop CS taxonomy research to combine its historical perspective, its current knowledge and its predicted future trends - including all breakthroughs in information and communication technology. In this paper we have analyzed the ACM Computing Classification System (CCS) by means of visualization maps. The important achievement of current work is an effective visualization of classified documents from the ACM Digital Library. From the technical point of view, the innovation lies in the parallel use of analysis units: (sub)classes and keywords as well as a spherical 3D information surface. We have compared both the thematic and semantic maps of classified documents and results presented in Table 1. Furthermore, the proposed new method is used for content-related evaluation of the original scheme. Summing up: we improved an original ACM classification in the Computer Science domain by means of visualization.

Date

22. 7.2010 19:36:46

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Abstract

Purpose - The purpose of this paper is to investigate user experiences with a touch-wall interface featuring both clustering and categorization representations of available e-books in a public library to understand human information interactions under work-focused and recreational contexts. Design/methodology/approach - Researchers collected questionnaires from 251 New Taipei City Library visitors who used the touch-wall interface to search for new titles. The authors applied structural equation modelling to examine relationships among hedonic/utilitarian needs, clustering and categorization representations, perceived ease of use (EU) and the extent to which users experienced anxiety and uncertainty (AU) while interacting with the interface. Findings - Utilitarian users who have an explicit idea of what they intend to find tend to prefer the categorization interface. A hedonic-oriented user tends to prefer clustering interfaces. Users reported EU regardless of which interface they engaged with. Results revealed that use of the clustering interface had a negative correlation with AU. Users that seek to satisfy utilitarian needs tended to emphasize the importance of perceived EU, whilst pleasure-seeking users were a little more tolerant of anxiety or uncertainty. Originality/value - The Online Public Access Catalogue (OPAC) encourages library visitors to borrow digital books through the implementation of an information visualization system. This situation poses an opportunity to validate uses and gratification theory. People with hedonic/utilitarian needs displayed different risk-control attitudes and affected uncertainty using the interface. Knowledge about user interaction with such interfaces is vital when launching the development of a new OPAC.

Date

20. 1.2015 18:30:22

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Date

23. 3.2008 19:10:22

Footnote

Rez. in: JASIST 54(2003) no.9, S.905-906 (C.A. Badurek): "Visual approaches for knowledge discovery in very large databases are a prime research need for information scientists focused an extracting meaningful information from the ever growing stores of data from a variety of domains, including business, the geosciences, and satellite and medical imagery. This work presents a summary of research efforts in the fields of data mining, knowledge discovery, and data visualization with the goal of aiding the integration of research approaches and techniques from these major fields. The editors, leading computer scientists from academia and industry, present a collection of 32 papers from contributors who are incorporating visualization and data mining techniques through academic research as well application development in industry and government agencies. Information Visualization focuses upon techniques to enhance the natural abilities of humans to visually understand data, in particular, large-scale data sets. It is primarily concerned with developing interactive graphical representations to enable users to more intuitively make sense of multidimensional data as part of the data exploration process. It includes research from computer science, psychology, human-computer interaction, statistics, and information science. Knowledge Discovery in Databases (KDD) most often refers to the process of mining databases for previously unknown patterns and trends in data. Data mining refers to the particular computational methods or algorithms used in this process. The data mining research field is most related to computational advances in database theory, artificial intelligence and machine learning. This work compiles research summaries from these main research areas in order to provide "a reference work containing the collection of thoughts and ideas of noted researchers from the fields of data mining and data visualization" (p. 8). It addresses these areas in three main sections: the first an data visualization, the second an KDD and model visualization, and the last an using visualization in the knowledge discovery process. The seven chapters of Part One focus upon methodologies and successful techniques from the field of Data Visualization. Hoffman and Grinstein (Chapter 2) give a particularly good overview of the field of data visualization and its potential application to data mining. An introduction to the terminology of data visualization, relation to perceptual and cognitive science, and discussion of the major visualization display techniques are presented. Discussion and illustration explain the usefulness and proper context of such data visualization techniques as scatter plots, 2D and 3D isosurfaces, glyphs, parallel coordinates, and radial coordinate visualizations. Remaining chapters present the need for standardization of visualization methods, discussion of user requirements in the development of tools, and examples of using information visualization in addressing research problems.
In 13 chapters, Part Two provides an introduction to KDD, an overview of data mining techniques, and examples of the usefulness of data model visualizations. The importance of visualization throughout the KDD process is stressed in many of the chapters. In particular, the need for measures of visualization effectiveness, benchmarking for identifying best practices, and the use of standardized sample data sets is convincingly presented. Many of the important data mining approaches are discussed in this complementary context. Cluster and outlier detection, classification techniques, and rule discovery algorithms are presented as the basic techniques common to the KDD process. The potential effectiveness of using visualization in the data modeling process are illustrated in chapters focused an using visualization for helping users understand the KDD process, ask questions and form hypotheses about their data, and evaluate the accuracy and veracity of their results. The 11 chapters of Part Three provide an overview of the KDD process and successful approaches to integrating KDD, data mining, and visualization in complementary domains. Rhodes (Chapter 21) begins this section with an excellent overview of the relation between the KDD process and data mining techniques. He states that the "primary goals of data mining are to describe the existing data and to predict the behavior or characteristics of future data of the same type" (p. 281). These goals are met by data mining tasks such as classification, regression, clustering, summarization, dependency modeling, and change or deviation detection. Subsequent chapters demonstrate how visualization can aid users in the interactive process of knowledge discovery by graphically representing the results from these iterative tasks. Finally, examples of the usefulness of integrating visualization and data mining tools in the domain of business, imagery and text mining, and massive data sets are provided. This text concludes with a thorough and useful 17-page index and lengthy yet integrating 17-page summary of the academic and industrial backgrounds of the contributing authors. A 16-page set of color inserts provide a better representation of the visualizations discussed, and a URL provided suggests that readers may view all the book's figures in color on-line, although as of this submission date it only provides access to a summary of the book and its contents. The overall contribution of this work is its focus an bridging two distinct areas of research, making it a valuable addition to the Morgan Kaufmann Series in Database Management Systems. The editors of this text have met their main goal of providing the first textbook integrating knowledge discovery, data mining, and visualization. Although it contributes greatly to our under- standing of the development and current state of the field, a major weakness of this text is that there is no concluding chapter to discuss the contributions of the sum of these contributed papers or give direction to possible future areas of research. "Integration of expertise between two different disciplines is a difficult process of communication and reeducation. Integrating data mining and visualization is particularly complex because each of these fields in itself must draw an a wide range of research experience" (p. 300). Although this work contributes to the crossdisciplinary communication needed to advance visualization in KDD, a more formal call for an interdisciplinary research agenda in a concluding chapter would have provided a more satisfying conclusion to a very good introductory text.
With contributors almost exclusively from the computer science field, the intended audience of this work is heavily slanted towards a computer science perspective. However, it is highly readable and provides introductory material that would be useful to information scientists from a variety of domains. Yet, much interesting work in information visualization from other fields could have been included giving the work more of an interdisciplinary perspective to complement their goals of integrating work in this area. Unfortunately, many of the application chapters are these, shallow, and lack complementary illustrations of visualization techniques or user interfaces used. However, they do provide insight into the many applications being developed in this rapidly expanding field. The authors have successfully put together a highly useful reference text for the data mining and information visualization communities. Those interested in a good introduction and overview of complementary research areas in these fields will be satisfied with this collection of papers. The focus upon integrating data visualization with data mining complements texts in each of these fields, such as Advances in Knowledge Discovery and Data Mining (Fayyad et al., MIT Press) and Readings in Information Visualization: Using Vision to Think (Card et. al., Morgan Kauffman). This unique work is a good starting point for future interaction between researchers in the fields of data visualization and data mining and makes a good accompaniment for a course focused an integrating these areas or to the main reference texts in these fields."

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Abstract

The Library of Congress Subject Headings (LCSH) has been developed over the course of more than a century, predating the semantic web by some time. Until the 1986, the only concept-toconcept relationship available was an undifferentiated "See Also" reference, which was used for both associative (RT) and hierarchical (BT/NT) connections. In that year, in preparation for the first release of the headings in machine readable MARC Authorities form, an attempt was made to automatically convert these "See Also" links into the standardized thesaural relations. Unfortunately, the rule used to determine the type of reference to generate relied on the presence of symmetric links to detect associatively related terms; "See Also" references that were only present in one of the related terms were assumed to be hierarchical. This left the process vulnerable to inconsistent use of references in the pre-conversion data, with a marked bias towards promoting relationships to hierarchical status. The Library of Congress was aware that the results of the conversion contained many inconsistencies, and intended to validate and correct the results over the course of time. Unfortunately, twenty years later, less than 40% of the converted records have been evaluated. The converted records, being the earliest encountered during the Library's cataloging activities, represent the most basic concepts within LCSH; errors in the syndetic structure for these records affect far more subordinate concepts than those nearer the periphery. Worse, a policy of patterning new headings after pre-existing ones leads to structural errors arising from the conversion process being replicated in these newer headings, perpetuating and exacerbating the errors. As the LCSH prepares for its second great conversion, from MARC to SKOS, it is critical to address these structural problems. As part of the work on converting the headings into SKOS, I have experimented with different visualizations of the tangled web of broader terms embedded in LCSH. This poster illustrates several of these renderings, shows how they can help users to judge which relationships might not be correct, and shows just exactly how Doorbells and Mammals are related.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

Conceptual modeling of bibliographic data, including the FR models and the consolidated IFLA LRM, has provided an opportunity to shift focus to entities and relationships and to support hierarchical work-based exploration of bibliographic information. This paper reports on a study examining the complexity of a work's bibliographic family data and user interactions with data visualizations, compared to traditional displays. Findings suggest that the FRBR-based visual bibliographic information system supports work families of different complexities more equally than a traditional system. Differences between the two systems also show that the FRBR-based system was more effective especially for related-works and author-related tasks.

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Date

30. 5.2010 16:22:35

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Date

1. 2.2016 18:25:22

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Abstract

The first of two articles discusses virtual reality (VR) and online databases; the second one reports on an interview with Thomas A. Furness III, who defines VR and explains work at the Human Interface Technology Laboratory (HIT). Sidebars contain a glossary of VR terms and a conversation with Toni Emerson, the HIT lab's librarian.

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Date

22. 1.2017 16:54:03
22. 1.2017 17:10:56

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Abstract

Purpose - Despite the importance of bibliographic information systems for discovering and exploring library resources, some of the core functionality that should be provided to support users in their information seeking process is still missing. Investigating these issues, the purpose of this paper is to design a solution that would fulfil the missing objectives. Design/methodology/approach - Building on the concepts of a work family, functional requirements for bibliographic records (FRBR) and information visualization, the paper proposes a model and user interface design that could support a more efficient and user-friendly presentation and navigation in bibliographic information systems. Findings - The proposed design brings together all versions of a work, related works, and other works by and about the author and shows how the model was implemented into a FrbrVis prototype system using hierarchical visualization layout. Research limitations/implications - Although issues related to discovery and exploration apply to various material types, the research first focused on works of fiction and was also limited by the selected sample of records. Practical implications - The model for presenting and interacting with FRBR-based data can serve as a good starting point for future developments and implementations. Originality/value - With FRBR concepts being gradually integrated into cataloguing rules, formats, and various bibliographic services, one of the important questions that has not really been investigated and studied is how the new type of data would be presented to users in a way that would exploit the true potential of the changes.

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Abstract

Since their beginnings, bibliographic information systems have been displaying results in the form of long, textual lists. With the development of new data models and computer technologies, the need for new approaches to present and interact with bibliographic data has slowly been maturing. To investigate how this could be accomplished, a prototype system, FrbrVis1, was designed to present work families within a bibliographic information system using information visualization. This paper reports on two user studies, a controlled and an observational experiment, that have been carried out to assess the Functional Requirements for Bibliographic Records (FRBR)-based against an existing system as well as to test four different hierarchical visual layouts. The results clearly show that FrbrVis offers better performance and user experience compared to the baseline system. The differences between the four hierarchical visualizations (Indented tree, Radial tree, Circlepack, and Sunburst) were, on the other hand, not as pronounced, but the Indented tree and Sunburst design proved to be the most successful, both in performance as well as user perception. The paper therefore not only evaluates the application of a visual presentation of bibliographic work families, but also provides valuable results regarding the performance and user acceptance of individual hierarchical visualization techniques.

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Abstract

This paper examines some traditional information searching methods and their role in Hungarian OPACs. What challenges are there in the digital and online environment? How do users work with them and do they give users satisfactory results? What kinds of techniques are users employing? In this paper I examine the user interfaces of UDC, thesauri, subject headings etc. in the Hungarian library. The key question of the paper is whether a universal system or local solutions is the best approach for searching in the digital environment.

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Date

30. 1.2007 18:22:41

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Abstract

The use of research impact metrics and analytics has become an integral component to many aspects of institutional assessment. Many platforms currently exist to provide such analytics, both proprietary and open source; however, the functionality of these systems may not always overlap to serve uniquely specific needs. In this paper, I describe a novel web-based platform, named Manifold, that I built to serve custom research impact assessment needs in the University of Minnesota Medical School. Built on a standard LAMP architecture, Manifold automatically pulls publication data for faculty from Scopus through APIs, calculates impact metrics through automated analytics, and dynamically generates report-like profiles that visualize those metrics. Work on this project has resulted in many lessons learned about challenges to sustainability and scalability in developing a system of such magnitude.

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Abstract

Children seek information in order to complete school projects on a wide variety of topics, as well as to support their various leisure activities. Such information can be found in print documents, but increasingly young people are turning to the Web to meet their information needs. In order to exploit this resource, however, children must be able to search or browse digital information through the intermediation of an interface. In particular, they must use Web-based portals that in most cases have been designed for adult users. Guidelines for interface design are not hard to find, but typically they also postulate adult rather than juvenile users. The authors discuss their own research work that has focused upon what young people themselves have to say about the design of portal interfaces. They conclude that specific interface design guidelines are required for young users rather than simply relying upon general design guidelines, and that in order to formulate such guidelines it is necessary to actively include the young people themselves in this process.

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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".

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Date

22. 3.2008 14:35:21

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Date

4. 2.2015 9:22:39

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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.