Search (5 results, page 1 of 1)

  • × theme_ss:"Semantic Web"
  • × theme_ss:"Wissensrepräsentation"
  • × type_ss:"x"
  1. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.17 
    0.17393503 = product of:
  0.21741877 = sum of:
    0.04909682 = product of:
      0.14729045 = sum of:
        0.14729045 = weight(_text_:3a in 701) [ClassicSimilarity], result of:
          0.14729045 = score(doc=701,freq=2.0), product of:
            0.39311135 = queryWeight, product of:
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.046368346 = queryNorm
            0.3746787 = fieldWeight in 701, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              8.478011 = idf(docFreq=24, maxDocs=44218)
              0.03125 = fieldNorm(doc=701)
      0.33333334 = coord(1/3)
    0.01155891 = weight(_text_:a in 701) [ClassicSimilarity], result of:
      0.01155891 = score(doc=701,freq=36.0), product of:
        0.053464882 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046368346 = queryNorm
        0.2161963 = fieldWeight in 701, product of:
          6.0 = tf(freq=36.0), with freq of:
            36.0 = termFreq=36.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=701)
    0.14729045 = weight(_text_:2f in 701) [ClassicSimilarity], result of:
      0.14729045 = score(doc=701,freq=2.0), product of:
        0.39311135 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.046368346 = queryNorm
        0.3746787 = fieldWeight in 701, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.03125 = fieldNorm(doc=701)
    0.009472587 = product of:
      0.018945174 = sum of:
        0.018945174 = weight(_text_:information in 701) [ClassicSimilarity], result of:
          0.018945174 = score(doc=701,freq=18.0), product of:
            0.08139861 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046368346 = queryNorm
            0.23274568 = fieldWeight in 701, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=701)
      0.5 = coord(1/2)
  0.8 = coord(4/5)
    Abstract
    By the explosion of possibilities for a ubiquitous content production, the information overload problem reaches the level of complexity which cannot be managed by traditional modelling approaches anymore. Due to their pure syntactical nature traditional information retrieval approaches did not succeed in treating content itself (i.e. its meaning, and not its representation). This leads to a very low usefulness of the results of a retrieval process for a user's task at hand. In the last ten years ontologies have been emerged from an interesting conceptualisation paradigm to a very promising (semantic) modelling technology, especially in the context of the Semantic Web. From the information retrieval point of view, ontologies enable a machine-understandable form of content description, such that the retrieval process can be driven by the meaning of the content. However, the very ambiguous nature of the retrieval process in which a user, due to the unfamiliarity with the underlying repository and/or query syntax, just approximates his information need in a query, implies a necessity to include the user in the retrieval process more actively in order to close the gap between the meaning of the content and the meaning of a user's query (i.e. his information need). This thesis lays foundation for such an ontology-based interactive retrieval process, in which the retrieval system interacts with a user in order to conceptually interpret the meaning of his query, whereas the underlying domain ontology drives the conceptualisation process. In that way the retrieval process evolves from a query evaluation process into a highly interactive cooperation between a user and the retrieval system, in which the system tries to anticipate the user's information need and to deliver the relevant content proactively. Moreover, the notion of content relevance for a user's query evolves from a content dependent artefact to the multidimensional context-dependent structure, strongly influenced by the user's preferences. This cooperation process is realized as the so-called Librarian Agent Query Refinement Process. In order to clarify the impact of an ontology on the retrieval process (regarding its complexity and quality), a set of methods and tools for different levels of content and query formalisation is developed, ranging from pure ontology-based inferencing to keyword-based querying in which semantics automatically emerges from the results. Our evaluation studies have shown that the possibilities to conceptualize a user's information need in the right manner and to interpret the retrieval results accordingly are key issues for realizing much more meaningful information retrieval systems.
    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  2. Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012) 0.01 
    0.007058388 = product of:
  0.01764597 = sum of:
    0.008173384 = weight(_text_:a in 3829) [ClassicSimilarity], result of:
      0.008173384 = score(doc=3829,freq=8.0), product of:
        0.053464882 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046368346 = queryNorm
        0.15287387 = fieldWeight in 3829, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=3829)
    0.009472587 = product of:
      0.018945174 = sum of:
        0.018945174 = weight(_text_:information in 3829) [ClassicSimilarity], result of:
          0.018945174 = score(doc=3829,freq=8.0), product of:
            0.08139861 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046368346 = queryNorm
            0.23274569 = fieldWeight in 3829, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=3829)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    In this thesis, we present an ontology-based information extraction and retrieval system and its application to soccer domain. In general, we deal with three issues in semantic search, namely, usability, scalability and retrieval performance. We propose a keyword-based semantic retrieval approach. The performance of the system is improved considerably using domain-specific information extraction, inference and rules. Scalability is achieved by adapting a semantic indexing approach. The system is implemented using the state-of-the-art technologies in SemanticWeb and its performance is evaluated against traditional systems as well as the query expansion methods. Furthermore, a detailed evaluation is provided to observe the performance gain due to domain-specific information extraction and inference. Finally, we show how we use semantic indexing to solve simple structural ambiguities.
    Source
    Information Systems. 37(2012) no. 4, S.294-305
    Type
    a
  3. Hüsken, P.: Information Retrieval im Semantic Web (2006) 0.00 
    0.0013396261 = product of:
  0.0066981306 = sum of:
    0.0066981306 = product of:
      0.013396261 = sum of:
        0.013396261 = weight(_text_:information in 4333) [ClassicSimilarity], result of:
          0.013396261 = score(doc=4333,freq=4.0), product of:
            0.08139861 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046368346 = queryNorm
            0.16457605 = fieldWeight in 4333, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=4333)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Abstract
    Das Semantic Web bezeichnet ein erweitertes World Wide Web (WWW), das die Bedeutung von präsentierten Inhalten in neuen standardisierten Sprachen wie RDF Schema und OWL modelliert. Diese Arbeit befasst sich mit dem Aspekt des Information Retrieval, d.h. es wird untersucht, in wie weit Methoden der Informationssuche sich auf modelliertes Wissen übertragen lassen. Die kennzeichnenden Merkmale von IR-Systemen wie vage Anfragen sowie die Unterstützung unsicheren Wissens werden im Kontext des Semantic Web behandelt. Im Fokus steht die Suche nach Fakten innerhalb einer Wissensdomäne, die entweder explizit modelliert sind oder implizit durch die Anwendung von Inferenz abgeleitet werden können. Aufbauend auf der an der Universität Duisburg-Essen entwickelten Retrievalmaschine PIRE wird die Anwendung unsicherer Inferenz mit probabilistischer Prädikatenlogik (pDatalog) implementiert.
  4. Meyer, A.: Begriffsrelationen im Kategoriensystem der Wikipedia : Entwicklung eines Relationeninventars zur kollaborativen Anwendung (2010) 0.00 
    6.8111526E-4 = product of:
  0.0034055763 = sum of:
    0.0034055763 = weight(_text_:a in 4429) [ClassicSimilarity], result of:
      0.0034055763 = score(doc=4429,freq=2.0), product of:
        0.053464882 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046368346 = queryNorm
        0.06369744 = fieldWeight in 4429, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4429)
  0.2 = coord(1/5)
  5. Botana Varela, J.: Unscharfe Wissensrepräsentationen bei der Implementation des Semantic Web (2004) 0.00 
    6.315058E-4 = product of:
  0.003157529 = sum of:
    0.003157529 = product of:
      0.006315058 = sum of:
        0.006315058 = weight(_text_:information in 3359) [ClassicSimilarity], result of:
          0.006315058 = score(doc=3359,freq=2.0), product of:
            0.08139861 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046368346 = queryNorm
            0.0775819 = fieldWeight in 3359, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=3359)
      0.5 = coord(1/2)
  0.2 = coord(1/5)
    Abstract
    In der vorliegenden Arbeit soll einen Ansatz zur Implementation einer Wissensrepräsentation mit den in Abschnitt 1.1. skizzierten Eigenschaften und dem Semantic Web als Anwendungsbereich vorgestellt werden. Die Arbeit ist im Wesentlichen in zwei Bereiche gegliedert: dem Untersuchungsbereich (Kapitel 2-5), in dem ich die in Abschnitt 1.1. eingeführte Terminologie definiert und ein umfassender Überblick über die zugrundeliegenden Konzepte gegeben werden soll, und dem Implementationsbereich (Kapitel 6), in dem aufbauend auf dem im Untersuchungsbereich erarbeiteten Wissen einen semantischen Suchdienst entwickeln werden soll. In Kapitel 2 soll zunächst das Konzept der semantischen Interpretation erläutert und in diesem Kontext hauptsächlich zwischen Daten, Information und Wissen unterschieden werden. In Kapitel 3 soll Wissensrepräsentation aus einer kognitiven Perspektive betrachtet und in diesem Zusammenhang das Konzept der Unschärfe beschrieben werden. In Kapitel 4 sollen sowohl aus historischer als auch aktueller Sicht die Ansätze zur Wissensrepräsentation und -auffindung beschrieben und in diesem Zusammenhang das Konzept der Unschärfe diskutiert werden. In Kapitel 5 sollen die aktuell im WWW eingesetzten Modelle und deren Einschränkungen erläutert werden. Anschließend sollen im Kontext der Entscheidungsfindung die Anforderungen beschrieben werden, die das WWW an eine adäquate Wissensrepräsentation stellt, und anhand der Technologien des Semantic Web die Repräsentationsparadigmen erläutert werden, die diese Anforderungen erfüllen. Schließlich soll das Topic Map-Paradigma erläutert werden. In Kapitel 6 soll aufbauend auf die im Untersuchtungsbereich gewonnenen Erkenntnisse ein Prototyp entwickelt werden. Dieser besteht im Wesentlichen aus Softwarewerkzeugen, die das automatisierte und computergestützte Extrahieren von Informationen, das unscharfe Modellieren, sowie das Auffinden von Wissen unterstützen. Die Implementation der Werkzeuge erfolgt in der Programmiersprache Java, und zur unscharfen Wissensrepräsentation werden Topic Maps eingesetzt. Die Implementation wird dabei schrittweise vorgestellt. Schließlich soll der Prototyp evaluiert und ein Ausblick auf zukünftige Erweiterungsmöglichkeiten gegeben werden. Und schließlich soll in Kapitel 7 eine Synthese formuliert werden.

Authors

Years

Languages

Types