Search (3 results, page 1 of 1)

0.042682633 = product of:
  0.085365266 = sum of:
    0.02277285 = weight(_text_:information in 758) [ClassicSimilarity], result of:
      0.02277285 = score(doc=758,freq=22.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.25731003 = fieldWeight in 758, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=758)
    0.06259242 = weight(_text_:standards in 758) [ClassicSimilarity], result of:
      0.06259242 = score(doc=758,freq=4.0), product of:
        0.22470023 = queryWeight, product of:
          4.4569545 = idf(docFreq=1393, maxDocs=44218)
          0.050415643 = queryNorm
        0.27855965 = fieldWeight in 758, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.4569545 = idf(docFreq=1393, maxDocs=44218)
          0.03125 = fieldNorm(doc=758)
  0.5 = coord(2/4)

Abstract

Innovative research institutes rely on the availability of complete and accurate information about new research and development, and it is the business of information providers such as Elsevier to provide the required information in a cost-effective way. It is very likely that the semantic web will make an important contribution to this effort, since it facilitates access to an unprecedented quantity of data. However, with the unremitting growth of scientific information, integrating access to all this information remains a significant problem, not least because of the heterogeneity of the information sources involved - sources which may use different syntactic standards (syntactic heterogeneity), organize information in very different ways (structural heterogeneity) and even use different terminologies to refer to the same information (semantic heterogeneity). The ability to address these different kinds of heterogeneity is the key to integrated access. Thesauri have already proven to be a core technology to effective information access as they provide controlled vocabularies for indexing information, and thereby help to overcome some of the problems of free-text search by relating and grouping relevant terms in a specific domain. However, currently there is no open architecture which supports the use of these thesauri for querying other data sources. For example, when we move from the centralized and controlled use of EMTREE within EMBASE.com to a distributed setting, it becomes crucial to improve access to the thesaurus by means of a standardized representation using open data standards that allow for semantic qualifications. In general, mental models and keywords for accessing data diverge between subject areas and communities, and so many different ontologies have been developed. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. The aim of the DOPE project (Drug Ontology Project for Elsevier) is to investigate the possibility of providing access to multiple information sources in the area of life science through a single interface.

0.006068985 = product of:
  0.02427594 = sum of:
    0.02427594 = weight(_text_:information in 2789) [ClassicSimilarity], result of:
      0.02427594 = score(doc=2789,freq=16.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.27429342 = fieldWeight in 2789, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2789)
  0.25 = coord(1/4)

Classification

ST 515 Informatik / Monographien / Einzelne Anwendungen der Datenverarbeitung / Wirtschaftsinformatik / Wissensmanagement, Information engineering

LCSH

Ontologies (Information retrieval)

RSWK

Semantic Web / Ontologie <Wissensverarbeitung> / Information Retrieval / Verteilung / Metadaten / Datenintegration

RVK

ST 515 Informatik / Monographien / Einzelne Anwendungen der Datenverarbeitung / Wirtschaftsinformatik / Wissensmanagement, Information engineering

Series

Advanced information and knowledge processing

Subject

Semantic Web / Ontologie <Wissensverarbeitung> / Information Retrieval / Verteilung / Metadaten / Datenintegration
Ontologies (Information retrieval)

0.0042914203 = product of:
  0.017165681 = sum of:
    0.017165681 = weight(_text_:information in 4403) [ClassicSimilarity], result of:
      0.017165681 = score(doc=4403,freq=8.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.19395474 = fieldWeight in 4403, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4403)
  0.25 = coord(1/4)

Abstract

The resource description framework (RDF) is a W3C recommendation for the formulation of meta-data on the World Wide Web. RDF Schema (RDFS) extends this standard with the means to specify domain vocabulary and object structures. These techniques will enable the enrichment of the Web with machine-processable semantics, thus giving rise to what has been dubbed the Semantic Web. We have developed Sesame, an architecture for storage and querying of RDF and RDFS information. Sesame allows persistent storage of RDF data and schema information, and provides access methods to that information through export and querying modules. It features ways of caching information and offers support for concurrency control. This chapter is organized as follows: In Section 5.2 we discuss why a query language specifically tailored to RDF and RDFS is needed, over and above existing query languages such as XQuery. In Section 5.3 we look at Sesame's modular architecture in some detail. In Section 5.4 we give an overview of the SAIL API and a brief comparison to other RDF API approaches. Section 5.5 discusses our experiences with Sesame to date, and Section 5.6 looks into possible future developments. Finally, we provide our conclusions in Section 5.7.