Search (65 results, page 4 of 4)

7.620421E-4 = product of:
  0.0022861264 = sum of:
    0.0022861264 = product of:
      0.011430631 = sum of:
        0.011430631 = weight(_text_:2 in 5329) [ClassicSimilarity], result of:
          0.011430631 = score(doc=5329,freq=2.0), product of:
            0.10473217 = queryWeight, product of:
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.042408705 = queryNorm
            0.10914155 = fieldWeight in 5329, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.03125 = fieldNorm(doc=5329)
      0.2 = coord(1/5)
  0.33333334 = coord(1/3)

Abstract

This book describes efficient and effective techniques for harnessing the power of Linked Data by tackling the various aspects of managing its growing volume: storing, querying, reasoning, provenance management and benchmarking. To this end, Chapter 1 introduces the main concepts of the Semantic Web and Linked Data and provides a roadmap for the book. Next, Chapter 2 briefly presents the basic concepts underpinning Linked Data technologies that are discussed in the book. Chapter 3 then offers an overview of various techniques and systems for centrally querying RDF datasets, and Chapter 4 outlines various techniques and systems for efficiently querying large RDF datasets in distributed environments. Subsequently, Chapter 5 explores how streaming requirements are addressed in current, state-of-the-art RDF stream data processing. Chapter 6 covers performance and scaling issues of distributed RDF reasoning systems, while Chapter 7 details benchmarks for RDF query engines and instance matching systems. Chapter 8 addresses the provenance management for Linked Data and presents the different provenance models developed. Lastly, Chapter 9 offers a brief summary, highlighting and providing insights into some of the open challenges and research directions. Providing an updated overview of methods, technologies and systems related to Linked Data this book is mainly intended for students and researchers who are interested in the Linked Data domain. It enables students to gain an understanding of the foundations and underpinning technologies and standards for Linked Data, while researchers benefit from the in-depth coverage of the emerging and ongoing advances in Linked Data storing, querying, reasoning, and provenance management systems. Further, it serves as a starting point to tackle the next research challenges in the domain of Linked Data management.

6.6678686E-4 = product of:
  0.0020003605 = sum of:
    0.0020003605 = product of:
      0.010001803 = sum of:
        0.010001803 = weight(_text_:2 in 4285) [ClassicSimilarity], result of:
          0.010001803 = score(doc=4285,freq=2.0), product of:
            0.10473217 = queryWeight, product of:
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.042408705 = queryNorm
            0.09549886 = fieldWeight in 4285, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4285)
      0.2 = coord(1/5)
  0.33333334 = coord(1/3)

Abstract

Um aus diesen beiden unabhangigen Systemen zur Inhaltserschlieung ein einheitliches, multilinguales Recherchevokabular zu bilden wurden im Rahmen des CrissCross Projekts unidirektionale Verbindungen von den einzelnen Sachschlagwortern der SWD zu den (teilweise) synthetisierten Notationen der DDC gescha en. Mittels dieser Verbindungen soll ein praziser und umfassender Zugang zu DDC-erschlossenen Dokumenten uber SWD-Schlagworter gewahrleistet werden. Da DDC-Notationen aber eher ihre Entsprechung in einer Kombination aus Schlagwortfolge und Sachgruppe haben, kann dieses Mapping in der Regel nur von SWD in Richtung DDC ausgewertet werden ohne dass ein groerer Informationsverlust auftritt. Deshalb haben die erstellten Mappings immer eine spezielle Verknupfungsrichtung, bei der die SWD als Ausgangsvokabular und die DDC als Zielvokabular dient. Das Dokument startet in Abschnitt 2 mit einem Uberblick uber die vier verschiedenen CrissCross-Mappingrelationen. Diese Mappingrelationen sollen im Rahmen einer Erweiterung fur die SKOS-Spezi kation4 semantisch reprasentiert werden. SKOS soll dabei sowohl benutzt werden, um die Konzepthierarchien der SWD und der DDC darzustellen als auch um die Mappings zwischen den beiden zu reprasentieren. Anhand von zwei konkreten Beispielen wird in Abschnitt 3 genauer erklart, welche Probleme insbesondere bei der Abbildung der CrissCross-Mappingrelationen mit Hilfe der SKOSSpezi kation auftreten. Insbesondere die Unidirektionalitat der ursprunglichen CrissCross-Mappings ist problematisch, da die in SKOS de nierten Mappingrelationen von einer Bidirektionalitat ausgehen. Das heit die Mappings mussen sowohl nutzbar sein fur die Suche in SWD-erschlossenen Bestanden als auch fur die Suche in DDC-erschlossenen Bestanden. Anhand der Beispiele in Abschnitt 3 wird deshalb auch eine initiale Losungsidee entwickelt, wie die Unidirektionalitat der CrissCross-Mappings aufgehoben werden kann.

6.6678686E-4 = product of:
  0.0020003605 = sum of:
    0.0020003605 = product of:
      0.010001803 = sum of:
        0.010001803 = weight(_text_:2 in 4205) [ClassicSimilarity], result of:
          0.010001803 = score(doc=4205,freq=2.0), product of:
            0.10473217 = queryWeight, product of:
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.042408705 = queryNorm
            0.09549886 = fieldWeight in 4205, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.02734375 = fieldNorm(doc=4205)
      0.2 = coord(1/5)
  0.33333334 = coord(1/3)

Abstract

Since the 90s, we have seen an explosion of information and with it there is an increase in the need for data and information aggregation systems that store and manage information. However, most of the information sources apply different Knowledge Organizations Systems (KOS) to describe the content of stored data. This heterogeneous mix of KOS in different systems complicate access and seamless sharing of information and knowledge. Concordances also known as cross-concordances or terminology mappings map different (KOS) to each other for improvement of information retrieval in such heterogeneous mix of systems. (Mayr 2010, Keil 2012). Also for coherent indexing with different terminologies, mappings are considered to be a valuable and essential working tool. However, despite efforts at standardization (e.g. SKOS, ISO 25964-2, Keil 2012, Soergel 2011); there is a significant scarcity of concordances that has led an inability to establish uniform exchange formats as well as methods and tools for maintaining mappings and making them easily accessible. This is particularly true in the field of library classification schemes. In essence, there is a lack of infrastructure for provision/exchange of concordances, their management and quality assessment as well as tools that would enable semi-automatic generation of mappings. The project "coli-conc" therefore aims to address this gap by creating the necessary infrastructure. This includes the specification of a data format for exchange of concordances (JSKOS), specification and implementation of web APIs to query concordance databases (JSKOS-API), and a modular web application to enable uniform access to knowledge organization systems, concordances and concordance assessments (Cocoda).

4.7627633E-4 = product of:
  0.0014288289 = sum of:
    0.0014288289 = product of:
      0.0071441447 = sum of:
        0.0071441447 = weight(_text_:2 in 3370) [ClassicSimilarity], result of:
          0.0071441447 = score(doc=3370,freq=2.0), product of:
            0.10473217 = queryWeight, product of:
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.042408705 = queryNorm
            0.06821347 = fieldWeight in 3370, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.01953125 = fieldNorm(doc=3370)
      0.2 = coord(1/5)
  0.33333334 = coord(1/3)

Content

Precombined subjects, such as those shown above from Dewey, may be expressed in UDC Summary as examples of combination within various records. To express an exact match UDC class 07 has to contain example of combination 07(7) Journals. The Press - North America. In some cases we have, therefore, added examples to UDC Summary that represent exact match to Dewey Summaries. It is unfortunate that DDC has so many classes on the top level that deal with a selection of countries or languages that are given a preferred status in the scheme, and repeating these preferences in examples of combinations of UDC emulates an unwelcome cultural bias which we have to balance out somehow. This brings us to another challenge.. UDC 913(7) Regional Geography - North America [contains 2 concepts each of which has its URI] is an exact match to Dewey 917 [represented as one concept, 1 URI]. It seems that, because they represent an exact match to Dewey numbers, these UDC examples of combinations may also need a separate URIs so that they can be published as SKOS data. Albeit challenging, mapping proves to be a very useful exercise and I am looking forward to future work here especially in relation to our plans to map UDC Summary to Colon Classification. We are discussing this project with colleagues from DRTC in Bangalore (India)."

4.7627633E-4 = product of:
  0.0014288289 = sum of:
    0.0014288289 = product of:
      0.0071441447 = sum of:
        0.0071441447 = weight(_text_:2 in 4315) [ClassicSimilarity], result of:
          0.0071441447 = score(doc=4315,freq=2.0), product of:
            0.10473217 = queryWeight, product of:
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.042408705 = queryNorm
            0.06821347 = fieldWeight in 4315, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.4695914 = idf(docFreq=10170, maxDocs=44218)
              0.01953125 = fieldNorm(doc=4315)
      0.2 = coord(1/5)
  0.33333334 = coord(1/3)

Content

Der zweite Tag begann mit einer Keynote von Dagobert Soergel von der University at Buffalo mit dem Thema Conceptual Foundations for Semantic Mapping and Semantic Search. Im Zentrum stand die Idee eines Hubs, einer semantischen Verbindungsstruktur in Form einer Kernklassifikation, die elementare Begriffe sowie semantische Relationen enthält und über die ein Mapping zwischen unterschiedlichen Wissensorganisationssystemen erfolgen soll. Die Methode wurde durch zahlreiche Beispiele veranschaulicht. Die erste Session des zweiten Tages war dem Thema Interoperabilität und Standardisierung gewidmet. Stella Dextre Clarke aus Großbritannien berichtete - ausgehend von den in zentralen Mappingprojekten erstellten Relationen zwischen Begriffen unterschiedlicher Dokumentationssprachen - über Herausforderungen und Fragestellungen bei der Entwicklung des neuen ISO-Standards 25964-2, der als Leitfaden zur Herstellung von Interoperabilität zwischen Thesauri und anderen Vokabularien fungieren soll. In dem Folgevortrag von Philipp Mayr vom GESIS Leipniz-Institut für Sozialwissenschaften wurd mit KoMoHe (Kompetenzzentrum Modellbildung und Heterogenitätsbehandlung) ein bereits abgeschlossenes Projekt vorgestellt, dessen Mehrwert für das Retrieval in heterogen erschlossenen Informationsräumen mittels eines Information-Retrieval-Tests bestätigt werden konnte. Unpräzise Trefferresultate motivierten indes zu dem Nachfolgeprojekt IRM (Value-Added Services for Information Retrieval), in dem Möglichkeiten von Suchexpansion und Re-Ranking untersucht werden.