Search (98 results, page 1 of 5)

  • × theme_ss:"Visualisierung"
  1. Burkhard, R.: Knowledge Visualization : Die nächste Herausforderung für Semantic Web Forschende? (2006) 0.09 
    0.08567109 = product of:
  0.21417773 = sum of:
    0.16374004 = weight(_text_:semantic in 5794) [ClassicSimilarity], result of:
      0.16374004 = score(doc=5794,freq=14.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.85078925 = fieldWeight in 5794, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5794)
    0.05043768 = product of:
      0.10087536 = sum of:
        0.10087536 = weight(_text_:web in 5794) [ClassicSimilarity], result of:
          0.10087536 = score(doc=5794,freq=14.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.6677857 = fieldWeight in 5794, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5794)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    Wer wird als erster die Vision des "Semantic Web" zur Realität machen? Vielleicht diejenigen Semantic Web Forschenden, die sich auf Knowledge Visualization konzentrieren. Dieser Artikel vermittelt einen ordnenden Überblick über das Thema Visualisierung für Semantic Web Forschende und beschreibt die wichtigen Perspektiven des optimalen Wissenstransfers. Der Artikel beschreibt die Vorteile von Visualisierungen und die Forschungsrichtungen, die für Semantic Web Forschende wichtig sind. Schließlich werden aktuelle Beispiele aus der Praxis, in denen das Nutzen, Finden oder Transferieren von Information eine Herausforderung war, beschrieben. Der Artikel vermittelt Praktikern in Firmen Lösungsansätze und zeigt Semantic Web Forschenden einen neuen Forschungsschwerpunkt, der nach der Etablierung von technischen Standards wichtig werden wird: Knowledge Visualization.
    Source
    Semantic Web: Wege zur vernetzten Wissensgesellschaft. Hrsg.: T. Pellegrini, u. A. Blumauer
  2. Singh, A.; Sinha, U.; Sharma, D.k.: Semantic Web and data visualization (2020) 0.07 
    0.06949035 = product of:
  0.17372587 = sum of:
    0.12750861 = weight(_text_:semantic in 79) [ClassicSimilarity], result of:
      0.12750861 = score(doc=79,freq=26.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.6625316 = fieldWeight in 79, product of:
          5.0990195 = tf(freq=26.0), with freq of:
            26.0 = termFreq=26.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.03125 = fieldNorm(doc=79)
    0.046217266 = product of:
      0.09243453 = sum of:
        0.09243453 = weight(_text_:web in 79) [ClassicSimilarity], result of:
          0.09243453 = score(doc=79,freq=36.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.6119082 = fieldWeight in 79, product of:
              6.0 = tf(freq=36.0), with freq of:
                36.0 = termFreq=36.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.03125 = fieldNorm(doc=79)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    With the terrific growth of data volume and data being produced every second on millions of devices across the globe, there is a desperate need to manage the unstructured data available on web pages efficiently. Semantic Web or also known as Web of Trust structures the scattered data on the Internet according to the needs of the user. It is an extension of the World Wide Web (WWW) which focuses on manipulating web data on behalf of Humans. Due to the ability of the Semantic Web to integrate data from disparate sources and hence makes it more user-friendly, it is an emerging trend. Tim Berners-Lee first introduced the term Semantic Web and since then it has come a long way to become a more intelligent and intuitive web. Data Visualization plays an essential role in explaining complex concepts in a universal manner through pictorial representation, and the Semantic Web helps in broadening the potential of Data Visualization and thus making it an appropriate combination. The objective of this chapter is to provide fundamental insights concerning the semantic web technologies and in addition to that it also elucidates the issues as well as the solutions regarding the semantic web. The purpose of this chapter is to highlight the semantic web architecture in detail while also comparing it with the traditional search system. It classifies the semantic web architecture into three major pillars i.e. RDF, Ontology, and XML. Moreover, it describes different semantic web tools used in the framework and technology. It attempts to illustrate different approaches of the semantic web search engines. Besides stating numerous challenges faced by the semantic web it also illustrates the solutions.
    Theme
    Semantic Web
  3. Aufreiter, M.: Informationsvisualisierung und Navigation im Semantic Web (2008) 0.07 
    0.067985155 = product of:
  0.16996288 = sum of:
    0.12993754 = weight(_text_:semantic in 4711) [ClassicSimilarity], result of:
      0.12993754 = score(doc=4711,freq=12.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.67515236 = fieldWeight in 4711, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.046875 = fieldNorm(doc=4711)
    0.04002533 = product of:
      0.08005066 = sum of:
        0.08005066 = weight(_text_:web in 4711) [ClassicSimilarity], result of:
          0.08005066 = score(doc=4711,freq=12.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.5299281 = fieldWeight in 4711, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=4711)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    Der Anreiz und das Potential von Informationsvisualisierungen wird bereits häufig erkannt und der Wunsch nach deren Anwendung immer stärker. Gerade im Bereich des Wissensmanagements spielt dieses Gebiet eine immer wichtigere Rolle. Diese Arbeit beschäftigt sich mit Informationsvisualisierung im Semantic Web und vermittelt einen Überblick über aktuelle Entwicklungen zum Thema Knowledge Visualization. Zun¨achst werden grundlegende Konzepte der Informationsvisualisierung vorgestellt und deren Bedeutung in Hinblick auf das Wissensmanagement erklärt. Aus den Anforderungen, die das Semantic Web an die Informationsvisualisierungen stellt, lassen sich Kriterien ableiten, die zur Beurteilung von Visualisierungstechniken herangezogen werden können. Die ausgewählten Kriterien werden im Rahmen dieser Arbeit zu einem Kriterienkatalog zusammengefasst. Schließlich werden ausgewählte Werkzeuge beschrieben, die im Wissensmanagement bereits erfolgreich Anwendung finden. Die einzelnen Untersuchungsobjekte werden nach einer detailierten Beschreibung anhand der ausgewählten Kriterien analysiert und bewertet. Dabei wird besonders auf deren Anwendung im Kontext des Semantic Web eingegangen.
    Source
    Eine Analyse bestehender Visualisierungstechniken im Hinblick auf Eignung für das Semantic Web
    Theme
    Semantic Web
  4. Zhang, J.; Mostafa, J.; Tripathy, H.: Information retrieval by semantic analysis and visualization of the concept space of D-Lib® magazine (2002) 0.06 
    0.061448015 = product of:
  0.10241336 = sum of:
    0.033088673 = weight(_text_:retrieval in 1211) [ClassicSimilarity], result of:
      0.033088673 = score(doc=1211,freq=16.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.23632148 = fieldWeight in 1211, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
    0.062516235 = weight(_text_:semantic in 1211) [ClassicSimilarity], result of:
      0.062516235 = score(doc=1211,freq=16.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.32483283 = fieldWeight in 1211, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.01953125 = fieldNorm(doc=1211)
    0.0068084467 = product of:
      0.013616893 = sum of:
        0.013616893 = weight(_text_:web in 1211) [ClassicSimilarity], result of:
          0.013616893 = score(doc=1211,freq=2.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.09014259 = fieldWeight in 1211, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.01953125 = fieldNorm(doc=1211)
      0.5 = coord(1/2)
  0.6 = coord(3/5)
    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
  5. Enser, P.: ¬The evolution of visual information retrieval (2009) 0.06 
    0.05684947 = product of:
  0.14212367 = sum of:
    0.080235764 = weight(_text_:retrieval in 3659) [ClassicSimilarity], result of:
      0.080235764 = score(doc=3659,freq=12.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.5730491 = fieldWeight in 3659, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3659)
    0.06188791 = weight(_text_:semantic in 3659) [ClassicSimilarity], result of:
      0.06188791 = score(doc=3659,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.32156807 = fieldWeight in 3659, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3659)
  0.4 = coord(2/5)
    Abstract
    This paper seeks to provide a brief overview of those developments which have taken the theory and practice of image and video retrieval into the digital age. Drawing on a voluminous literature, the context in which visual information retrieval takes place is followed by a consideration of the conceptual and practical challenges posed by the representation and recovery of visual material on the basis of its semantic content. An historical account of research endeavours in content-based retrieval, directed towards the automation of these operations in digital image scenarios, provides the main thrust of the paper. Finally, a look forwards locates visual information retrieval research within the wider context of content-based multimedia retrieval.
  6. Di Maio, P.: Linked data beyond libraries : towards universal interfaces and knowledge unification (2015) 0.06 
    0.055509638 = product of:
  0.1387741 = sum of:
    0.10609356 = weight(_text_:semantic in 2553) [ClassicSimilarity], result of:
      0.10609356 = score(doc=2553,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.5512596 = fieldWeight in 2553, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.09375 = fieldNorm(doc=2553)
    0.03268054 = product of:
      0.06536108 = sum of:
        0.06536108 = weight(_text_:web in 2553) [ClassicSimilarity], result of:
          0.06536108 = score(doc=2553,freq=2.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.43268442 = fieldWeight in 2553, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.09375 = fieldNorm(doc=2553)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Theme
    Semantic Web
  7. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.05 
    0.047907133 = product of:
  0.11976783 = sum of:
    0.0884113 = weight(_text_:semantic in 2755) [ClassicSimilarity], result of:
      0.0884113 = score(doc=2755,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.45938298 = fieldWeight in 2755, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.078125 = fieldNorm(doc=2755)
    0.031356532 = product of:
      0.062713064 = sum of:
        0.062713064 = weight(_text_:22 in 2755) [ClassicSimilarity], result of:
          0.062713064 = score(doc=2755,freq=2.0), product of:
            0.16209066 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04628742 = queryNorm
            0.38690117 = fieldWeight in 2755, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=2755)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
  8. Neubauer, G.: Visualization of typed links in linked data (2017) 0.05 
    0.046032332 = product of:
  0.115080826 = sum of:
    0.076566435 = weight(_text_:semantic in 3912) [ClassicSimilarity], result of:
      0.076566435 = score(doc=3912,freq=6.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.39783734 = fieldWeight in 3912, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3912)
    0.03851439 = product of:
      0.07702878 = sum of:
        0.07702878 = weight(_text_:web in 3912) [ClassicSimilarity], result of:
          0.07702878 = score(doc=3912,freq=16.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.5099235 = fieldWeight in 3912, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3912)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    Das Themengebiet der Arbeit behandelt Visualisierungen von typisierten Links in Linked Data. Die wissenschaftlichen Gebiete, die im Allgemeinen den Inhalt des Beitrags abgrenzen, sind das Semantic Web, das Web of Data und Informationsvisualisierung. Das Semantic Web, das von Tim Berners Lee 2001 erfunden wurde, stellt eine Erweiterung zum World Wide Web (Web 2.0) dar. Aktuelle Forschungen beziehen sich auf die Verknüpfbarkeit von Informationen im World Wide Web. Um es zu ermöglichen, solche Verbindungen wahrnehmen und verarbeiten zu können sind Visualisierungen die wichtigsten Anforderungen als Hauptteil der Datenverarbeitung. Im Zusammenhang mit dem Sematic Web werden Repräsentationen von zusammenhängenden Informationen anhand von Graphen gehandhabt. Der Grund des Entstehens dieser Arbeit ist in erster Linie die Beschreibung der Gestaltung von Linked Data-Visualisierungskonzepten, deren Prinzipien im Rahmen einer theoretischen Annäherung eingeführt werden. Anhand des Kontexts führt eine schrittweise Erweiterung der Informationen mit dem Ziel, praktische Richtlinien anzubieten, zur Vernetzung dieser ausgearbeiteten Gestaltungsrichtlinien. Indem die Entwürfe zweier alternativer Visualisierungen einer standardisierten Webapplikation beschrieben werden, die Linked Data als Netzwerk visualisiert, konnte ein Test durchgeführt werden, der deren Kompatibilität zum Inhalt hatte. Der praktische Teil behandelt daher die Designphase, die Resultate, und zukünftige Anforderungen des Projektes, die durch die Testung ausgearbeitet wurden.
    Theme
    Semantic Web
  9. Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009) 0.05 
    0.04572124 = product of:
  0.1143031 = sum of:
    0.07072904 = weight(_text_:semantic in 4870) [ClassicSimilarity], result of:
      0.07072904 = score(doc=4870,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.36750638 = fieldWeight in 4870, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0625 = fieldNorm(doc=4870)
    0.043574058 = product of:
      0.087148115 = sum of:
        0.087148115 = weight(_text_:web in 4870) [ClassicSimilarity], result of:
          0.087148115 = score(doc=4870,freq=8.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.5769126 = fieldWeight in 4870, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0625 = fieldNorm(doc=4870)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Object
    Web 2.0
    Source
    Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
  10. Spero, S.: LCSH is to thesaurus as doorbell is to mammal : visualizing structural problems in the Library of Congress Subject Headings (2008) 0.04 
    0.04236389 = product of:
  0.10590972 = sum of:
    0.050012987 = weight(_text_:semantic in 2659) [ClassicSimilarity], result of:
      0.050012987 = score(doc=2659,freq=4.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.25986627 = fieldWeight in 2659, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.03125 = fieldNorm(doc=2659)
    0.055896737 = sum of:
      0.030811511 = weight(_text_:web in 2659) [ClassicSimilarity], result of:
        0.030811511 = score(doc=2659,freq=4.0), product of:
          0.15105948 = queryWeight, product of:
            3.2635105 = idf(docFreq=4597, maxDocs=44218)
            0.04628742 = queryNorm
          0.2039694 = fieldWeight in 2659, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.2635105 = idf(docFreq=4597, maxDocs=44218)
            0.03125 = fieldNorm(doc=2659)
      0.025085226 = weight(_text_:22 in 2659) [ClassicSimilarity], result of:
        0.025085226 = score(doc=2659,freq=2.0), product of:
          0.16209066 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.04628742 = queryNorm
          0.15476047 = fieldWeight in 2659, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.03125 = fieldNorm(doc=2659)
  0.4 = coord(2/5)
    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
  11. Eckert, K.: Thesaurus analysis and visualization in semantic search applications (2007) 0.03 
    0.030917728 = product of:
  0.07729432 = sum of:
    0.033088673 = weight(_text_:retrieval in 3222) [ClassicSimilarity], result of:
      0.033088673 = score(doc=3222,freq=4.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.23632148 = fieldWeight in 3222, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3222)
    0.04420565 = weight(_text_:semantic in 3222) [ClassicSimilarity], result of:
      0.04420565 = score(doc=3222,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.22969149 = fieldWeight in 3222, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3222)
  0.4 = coord(2/5)
    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.
  12. Osinska, V.; Bala, P.: New methods for visualization and improvement of classification schemes : the case of computer science (2010) 0.03 
    0.02874428 = product of:
  0.0718607 = sum of:
    0.05304678 = weight(_text_:semantic in 3693) [ClassicSimilarity], result of:
      0.05304678 = score(doc=3693,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.2756298 = fieldWeight in 3693, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.046875 = fieldNorm(doc=3693)
    0.01881392 = product of:
      0.03762784 = sum of:
        0.03762784 = weight(_text_:22 in 3693) [ClassicSimilarity], result of:
          0.03762784 = score(doc=3693,freq=2.0), product of:
            0.16209066 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04628742 = queryNorm
            0.23214069 = fieldWeight in 3693, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=3693)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    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
  13. Chowdhury, S.; Chowdhury, G.G.: Using DDC to create a visual knowledge map as an aid to online information retrieval (2004) 0.03 
    0.028623639 = product of:
  0.071559094 = sum of:
    0.05615334 = weight(_text_:retrieval in 2643) [ClassicSimilarity], result of:
      0.05615334 = score(doc=2643,freq=18.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.40105084 = fieldWeight in 2643, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.03125 = fieldNorm(doc=2643)
    0.0154057555 = product of:
      0.030811511 = sum of:
        0.030811511 = weight(_text_:web in 2643) [ClassicSimilarity], result of:
          0.030811511 = score(doc=2643,freq=4.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.2039694 = fieldWeight in 2643, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.03125 = fieldNorm(doc=2643)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Content
    1. Introduction Web search engines and digital libraries usually expect the users to use search terms that most accurately represent their information needs. Finding the most appropriate search terms to represent an information need is an age old problem in information retrieval. Keyword or phrase search may produce good search results as long as the search terms or phrase(s) match those used by the authors and have been chosen for indexing by the concerned information retrieval system. Since this does not always happen, a large number of false drops are produced by information retrieval systems. The retrieval results become worse in very large systems that deal with millions of records, such as the Web search engines and digital libraries. Vocabulary control tools are used to improve the performance of text retrieval systems. Thesauri, the most common type of vocabulary control tool used in information retrieval, appeared in the late fifties, designed for use with the emerging post-coordinate indexing systems of that time. They are used to exert terminology control in indexing, and to aid in searching by allowing the searcher to select appropriate search terms. A large volume of literature exists describing the design features, and experiments with the use, of thesauri in various types of information retrieval systems (see for example, Furnas et.al., 1987; Bates, 1986, 1998; Milstead, 1997, and Shiri et al., 2002).
    Theme
    Klassifikationssysteme im Online-Retrieval
  14. Hajdu Barat, A.: Human perception and knowledge organization : visual imagery (2007) 0.03 
    0.02704115 = product of:
  0.06760287 = sum of:
    0.023397226 = weight(_text_:retrieval in 2595) [ClassicSimilarity], result of:
      0.023397226 = score(doc=2595,freq=2.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.16710453 = fieldWeight in 2595, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2595)
    0.04420565 = weight(_text_:semantic in 2595) [ClassicSimilarity], result of:
      0.04420565 = score(doc=2595,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.22969149 = fieldWeight in 2595, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2595)
  0.4 = coord(2/5)
    Abstract
    Purpose - This paper aims to explore the theory and practice of knowledge organization and its necessary connection to human perception, and shows a solution of the potential ones. Design/methodology/approach - The author attempts to survey the problem of concept-building and extension, as well as the determination of semantics in different aspects. The purpose is to find criteria for the choice of the solution that best incorporates users into the design cycles of knowledge organization systems. Findings - It is widely agreed that cognition provides the basis for concept-building; however, at the next stage of processing there is a debate. Fundamentally, what is the connection between perception and the superior cognitive processes? The perceptual method does not separate these two but rather considers them united, with perception permeating cognition. By contrast, the linguistic method considers perception as an information-receiving system. Separate from, and following, perception, the cognitive subsystems then perform information and data processing, leading to both knowledge organization and representation. We assume by that model that top-level concepts emerge from knowledge organization and representation. This paper points obvious connection of visual imagery and the internet; perceptual access of knowledge organization and information retrieval. There are some practical and characteristic solutions for the visualization of information without demand of completeness. Research limitations/implications - Librarians need to identify those semantic characteristics which stimulate a similar conceptual image both in the mind of the librarian and in the mind of the user. Originality/value - For a fresh perspective, an understanding of perception is required as well.
  15. Darányi, S.; Wittek, P.: Demonstrating conceptual dynamics in an evolving text collection (2013) 0.03 
    0.02704115 = product of:
  0.06760287 = sum of:
    0.023397226 = weight(_text_:retrieval in 1137) [ClassicSimilarity], result of:
      0.023397226 = score(doc=1137,freq=2.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.16710453 = fieldWeight in 1137, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1137)
    0.04420565 = weight(_text_:semantic in 1137) [ClassicSimilarity], result of:
      0.04420565 = score(doc=1137,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.22969149 = fieldWeight in 1137, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1137)
  0.4 = coord(2/5)
    Abstract
    Based on real-world user demands, we demonstrate how animated visualization of evolving text corpora displays the underlying dynamics of semantic content. To interpret the results, one needs a dynamic theory of word meaning. We suggest that conceptual dynamics as the interaction between kinds of intellectual and emotional content and language is key for such a theory. We demonstrate our method by two-way seriation, which is a popular technique to analyze groups of similar instances and their features as well as the connections between the groups themselves. The two-way seriated data may be visualized as a two-dimensional heat map or as a three-dimensional landscape in which color codes or height correspond to the values in the matrix. In this article, we focus on two-way seriation of sparse data in the Reuters-21568 test collection. To achieve a meaningful visualization, we introduce a compactly supported convolution kernel similar to filter kernels used in image reconstruction and geostatistics. This filter populates the high-dimensional sparse space with values that interpolate nearby elements and provides insight into the clustering structure. We also extend two-way seriation to deal with online updates of both the row and column spaces and, combined with the convolution kernel, demonstrate a three-dimensional visualization of dynamics.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Jäger-Dengler-Harles, I.: Informationsvisualisierung und Retrieval im Fokus der Infromationspraxis (2013) 0.03 
    0.026977658 = product of:
  0.067444146 = sum of:
    0.048630223 = weight(_text_:retrieval in 1709) [ClassicSimilarity], result of:
      0.048630223 = score(doc=1709,freq=6.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.34732026 = fieldWeight in 1709, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=1709)
    0.01881392 = product of:
      0.03762784 = sum of:
        0.03762784 = weight(_text_:22 in 1709) [ClassicSimilarity], result of:
          0.03762784 = score(doc=1709,freq=2.0), product of:
            0.16209066 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.04628742 = queryNorm
            0.23214069 = fieldWeight in 1709, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=1709)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    Methoden und Techniken der Informationsvisualisierung werden seit ungefähr zwanzig Jahren im Bereich der Informationssuche eingesetzt. In dieser Literaturstudie werden ausgewählte Visualisierungsanwendungen der letzten Jahre vorgestellt. Sie betreffen zum einen den Retrievalprozess, das Boolesche Retrieval, die facettierte Suche, Dokumentbeziehungen, die Zufallssuche und Ergebnisanzeige, zum anderen spezielle Anwendungen wie die kartenbasierte und adaptive Visualisierung, Zitationsnetzwerke und Wissensordnungen. Die Einsatzszenarien für Applikationen der Informationsvisualisierung sind vielfältig. Sie reichen von mobilen kleinformatigen Anwendungen bis zu großformatigen Darstellungen auf hochauflösenden Bildschirmen, von integrativen Arbeitsplätzen für den einzelnen Nutzer bis zur Nutzung interaktiver Oberflächen für das kollaborative Retrieval. Das Konzept der Blended Library wird vorgestellt. Die Übertragbarkeit von Visualisierungsanwendungen auf Bibliothekskataloge wird im Hinblick auf die Nutzung des Kataloginputs und des Angebots an Sucheinstiegen geprüft. Perspektivische Überlegungen zu zukünftigen Entwicklungsschritten von Bibliothekskatalogen sowie zum Einfluss von Visualisierungsanwendungen auf die Informationspraxis werden angestellt.
    Date
    4. 2.2015 9:22:39
  17. Given, L.M.; Ruecker, S.; Simpson, H.; Sadler, E.; Ruskin, A.: Inclusive interface design for seniors : Image-browsing for a health information context (2007) 0.03 
    0.026155118 = product of:
  0.06538779 = sum of:
    0.04632414 = weight(_text_:retrieval in 579) [ClassicSimilarity], result of:
      0.04632414 = score(doc=579,freq=4.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.33085006 = fieldWeight in 579, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0546875 = fieldNorm(doc=579)
    0.019063652 = product of:
      0.038127303 = sum of:
        0.038127303 = weight(_text_:web in 579) [ClassicSimilarity], result of:
          0.038127303 = score(doc=579,freq=2.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.25239927 = fieldWeight in 579, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=579)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    This study explores an image-based retrieval interface for drug information, focusing on usability for a specific population - seniors. Qualitative, task-based interviews examined participants' health information behaviors and documented search strategies using an existing database (www.drugs.com) and a new prototype that uses similarity-based clustering of pill images for retrieval. Twelve participants (aged 65 and older), reflecting a diversity of backgrounds and experience with Web-based resources, located pill information using the interfaces and discussed navigational and other search preferences. Findings point to design features (e.g., image enlargement) that meet seniors' needs in the context of other health-related information-seeking strategies (e.g., contacting pharmacists).
  18. Hearst, M.A.: Search user interfaces (2009) 0.02 
    0.02471768 = product of:
  0.0617942 = sum of:
    0.03743556 = weight(_text_:retrieval in 4029) [ClassicSimilarity], result of:
      0.03743556 = score(doc=4029,freq=8.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.26736724 = fieldWeight in 4029, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.03125 = fieldNorm(doc=4029)
    0.02435864 = product of:
      0.04871728 = sum of:
        0.04871728 = weight(_text_:web in 4029) [ClassicSimilarity], result of:
          0.04871728 = score(doc=4029,freq=10.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.32250395 = fieldWeight in 4029, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.03125 = fieldNorm(doc=4029)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    This book outlines the human side of the information seeking process, and focuses on the aspects of this process that can best be supported by the user interface. It describes the methods behind user interface design generally, and search interface design in particular, with an emphasis on how best to evaluate search interfaces. It discusses research results and current practices surrounding user interfaces for query specification, display of retrieval results, grouping retrieval results, navigation of information collections, query reformulation, search personalization, and the broader tasks of sensemaking and text analysis. Much of the discussion pertains to Web search engines, but the book also covers the special considerations surrounding search of other information collections.
    LCSH
    Web search engines
    RSWK
    World Wide Web / Information Retrieval / Mensch-Maschine-Kommunikation / Benutzerorientierung (HBZ)
    Subject
    World Wide Web / Information Retrieval / Mensch-Maschine-Kommunikation / Benutzerorientierung (HBZ)
    Web search engines
  19. Koch, T.; Golub, K.; Ardö, A.: Users browsing behaviour in a DDC-based Web service : a log analysis (2006) 0.02 
    0.024302885 = product of:
  0.060757212 = sum of:
    0.028076671 = weight(_text_:retrieval in 2234) [ClassicSimilarity], result of:
      0.028076671 = score(doc=2234,freq=2.0), product of:
        0.14001551 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.04628742 = queryNorm
        0.20052543 = fieldWeight in 2234, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=2234)
    0.03268054 = product of:
      0.06536108 = sum of:
        0.06536108 = weight(_text_:web in 2234) [ClassicSimilarity], result of:
          0.06536108 = score(doc=2234,freq=8.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.43268442 = fieldWeight in 2234, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.046875 = fieldNorm(doc=2234)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    This study explores the navigation behaviour of all users of a large web service, Renardus, using web log analysis. Renardus provides integrated searching and browsing access to quality-controlled web resources from major individual subject gateway services. The main navigation feature is subject browsing through the Dewey Decimal Classification (DDC) based on mapping of classes of resources from the distributed gateways to the DDC structure. Among the more surprising results are the hugely dominant share of browsing activities, the good use of browsing support features like the graphical fish-eye overviews, rather long and varied navigation sequences, as well as extensive hierarchical directory-style browsing through the large DDC system.
    Theme
    Klassifikationssysteme im Online-Retrieval
  20. Xiaoyue M.; Cahier, J.-P.: Iconic categorization with knowledge-based "icon systems" can improve collaborative KM (2011) 0.02 
    0.023129018 = product of:
  0.057822544 = sum of:
    0.04420565 = weight(_text_:semantic in 4837) [ClassicSimilarity], result of:
      0.04420565 = score(doc=4837,freq=2.0), product of:
        0.19245663 = queryWeight, product of:
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.04628742 = queryNorm
        0.22969149 = fieldWeight in 4837, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.1578603 = idf(docFreq=1879, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4837)
    0.013616893 = product of:
      0.027233787 = sum of:
        0.027233787 = weight(_text_:web in 4837) [ClassicSimilarity], result of:
          0.027233787 = score(doc=4837,freq=2.0), product of:
            0.15105948 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.04628742 = queryNorm
            0.18028519 = fieldWeight in 4837, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4837)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    Icon system could represent an efficient solution for collective iconic categorization of knowledge by providing graphical interpretation. Their pictorial characters assist visualizing the structure of text to become more understandable beyond vocabulary obstacle. In this paper we are proposing a Knowledge Engineering (KM) based iconic representation approach. We assume that these systematic icons improve collective knowledge management. Meanwhile, text (constructed under our knowledge management model - Hypertopic) helps to reduce the diversity of graphical understanding belonging to different users. This "position paper" also prepares to demonstrate our hypothesis by an "iconic social tagging" experiment which is to be accomplished in 2011 with UTT students. We describe the "socio semantic web" information portal involved in this project, and a part of the icons already designed for this experiment in Sustainability field. We have reviewed existing theoretical works on icons from various origins, which can be used to lay the foundation of robust "icons systems".

Authors

Years

Languages

  • e 74
  • d 23
  • a 1
  • More… Less…

Types

  • a 78
  • el 15
  • m 9
  • x 8
  • b 1
  • p 1
  • r 1
  • s 1
  • More… Less…

Themes

Subjects

Classifications