Search (75 results, page 1 of 4)

  • × language_ss:"e"
  • × theme_ss:"Semantic Web"
  • × type_ss:"el"
  1. Scheir, P.; Pammer, V.; Lindstaedt, S.N.: Information retrieval on the Semantic Web : does it exist? (2007) 0.06
    0.055867687 = product of:
      0.111735374 = sum of:
        0.058445733 = weight(_text_:retrieval in 4329) [ClassicSimilarity], result of:
          0.058445733 = score(doc=4329,freq=8.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.46789268 = fieldWeight in 4329, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4329)
        0.029945528 = weight(_text_:use in 4329) [ClassicSimilarity], result of:
          0.029945528 = score(doc=4329,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 4329, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4329)
        0.015619429 = weight(_text_:of in 4329) [ClassicSimilarity], result of:
          0.015619429 = score(doc=4329,freq=8.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.24188137 = fieldWeight in 4329, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4329)
        0.007724685 = product of:
          0.01544937 = sum of:
            0.01544937 = weight(_text_:on in 4329) [ClassicSimilarity], result of:
              0.01544937 = score(doc=4329,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.17010231 = fieldWeight in 4329, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4329)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    Plenty of contemporary attempts to search exist that are associated with the area of Semantic Web. But which of them qualify as information retrieval for the Semantic Web? Do such approaches exist? To answer these questions we take a look at the nature of the Semantic Web and Semantic Desktop and at definitions for information and data retrieval. We survey current approaches referred to by their authors as information retrieval for the Semantic Web or that use Semantic Web technology for search.
  2. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.05
    0.0530889 = product of:
      0.1061778 = sum of:
        0.06534432 = weight(_text_:retrieval in 4330) [ClassicSimilarity], result of:
          0.06534432 = score(doc=4330,freq=10.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.5231199 = fieldWeight in 4330, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4330)
        0.013526822 = weight(_text_:of in 4330) [ClassicSimilarity], result of:
          0.013526822 = score(doc=4330,freq=6.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.20947541 = fieldWeight in 4330, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4330)
        0.007724685 = product of:
          0.01544937 = sum of:
            0.01544937 = weight(_text_:on in 4330) [ClassicSimilarity], result of:
              0.01544937 = score(doc=4330,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.17010231 = fieldWeight in 4330, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4330)
          0.5 = coord(1/2)
        0.019581974 = product of:
          0.039163947 = sum of:
            0.039163947 = weight(_text_:22 in 4330) [ClassicSimilarity], result of:
              0.039163947 = score(doc=4330,freq=2.0), product of:
                0.1446067 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041294612 = queryNorm
                0.2708308 = fieldWeight in 4330, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=4330)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.
    Date
    12. 2.2011 17:35:22
  3. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.04
    0.042324685 = product of:
      0.08464937 = sum of:
        0.036299463 = weight(_text_:use in 4649) [ClassicSimilarity], result of:
          0.036299463 = score(doc=4649,freq=4.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.2870708 = fieldWeight in 4649, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=4649)
        0.022201622 = weight(_text_:of in 4649) [ClassicSimilarity], result of:
          0.022201622 = score(doc=4649,freq=22.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.34381276 = fieldWeight in 4649, product of:
              4.690416 = tf(freq=22.0), with freq of:
                22.0 = termFreq=22.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=4649)
        0.009363732 = product of:
          0.018727465 = sum of:
            0.018727465 = weight(_text_:on in 4649) [ClassicSimilarity], result of:
              0.018727465 = score(doc=4649,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.20619515 = fieldWeight in 4649, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4649)
          0.5 = coord(1/2)
        0.016784549 = product of:
          0.033569098 = sum of:
            0.033569098 = weight(_text_:22 in 4649) [ClassicSimilarity], result of:
              0.033569098 = score(doc=4649,freq=2.0), product of:
                0.1446067 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041294612 = queryNorm
                0.23214069 = fieldWeight in 4649, 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=4649)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    More and more cultural heritage institutions publish their collections, vocabularies and metadata on the Web. The resulting Web of linked cultural data opens up exciting new possibilities for searching and browsing through these cultural heritage collections. We report on ongoing work in which we investigate the estimation of relevance in this Web of Culture. We study existing measures of semantic distance and how they apply to two use cases. The use cases relate to the structured, multilingual and multimodal nature of the Culture Web. We distinguish between measures using the Web, such as Google distance and PMI, and measures using the Linked Data Web, i.e. the semantic structure of metadata vocabularies. We perform a small study in which we compare these semantic distance measures to human judgements of relevance. Although it is too early to draw any definitive conclusions, the study provides new insights into the applicability of semantic distance measures to the Web of Culture, and clear starting points for further research.
    Date
    26.12.2011 13:40:22
  4. Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004) 0.04
    0.041340277 = product of:
      0.08268055 = sum of:
        0.035423465 = weight(_text_:retrieval in 4704) [ClassicSimilarity], result of:
          0.035423465 = score(doc=4704,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.2835858 = fieldWeight in 4704, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=4704)
        0.025667597 = weight(_text_:use in 4704) [ClassicSimilarity], result of:
          0.025667597 = score(doc=4704,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 4704, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=4704)
        0.014968331 = weight(_text_:of in 4704) [ClassicSimilarity], result of:
          0.014968331 = score(doc=4704,freq=10.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.23179851 = fieldWeight in 4704, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=4704)
        0.006621159 = product of:
          0.013242318 = sum of:
            0.013242318 = weight(_text_:on in 4704) [ClassicSimilarity], result of:
              0.013242318 = score(doc=4704,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.14580199 = fieldWeight in 4704, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4704)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    Swoogle is a crawler-based indexing and retrieval system for the Semantic Web, i.e., for Web documents in RDF or OWL. It extracts metadata for each discovered document, and computes relations between documents. Discovered documents are also indexed by an information retrieval system which can use either character N-Gram or URIrefs as keywords to find relevant documents and to compute the similarity among a set of documents. One of the interesting properties we compute is rank, a measure of the importance of a Semantic Web document.
    Source
    CIKM '04 Proceedings of the thirteenth ACM international conference on Information and knowledge management
  5. Heflin, J.; Hendler, J.: Semantic interoperability on the Web (2000) 0.04
    0.041018434 = product of:
      0.08203687 = sum of:
        0.029945528 = weight(_text_:use in 759) [ClassicSimilarity], result of:
          0.029945528 = score(doc=759,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 759, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=759)
        0.019129815 = weight(_text_:of in 759) [ClassicSimilarity], result of:
          0.019129815 = score(doc=759,freq=12.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.29624295 = fieldWeight in 759, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=759)
        0.013379549 = product of:
          0.026759097 = sum of:
            0.026759097 = weight(_text_:on in 759) [ClassicSimilarity], result of:
              0.026759097 = score(doc=759,freq=6.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.29462588 = fieldWeight in 759, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=759)
          0.5 = coord(1/2)
        0.019581974 = product of:
          0.039163947 = sum of:
            0.039163947 = weight(_text_:22 in 759) [ClassicSimilarity], result of:
              0.039163947 = score(doc=759,freq=2.0), product of:
                0.1446067 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041294612 = queryNorm
                0.2708308 = fieldWeight in 759, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=759)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    XML will have a profound impact on the way data is exchanged on the Internet. An important feature of this language is the separation of content from presentation, which makes it easier to select and/or reformat the data. However, due to the likelihood of numerous industry and domain specific DTDs, those who wish to integrate information will still be faced with the problem of semantic interoperability. In this paper we discuss why this problem is not solved by XML, and then discuss why the Resource Description Framework is only a partial solution. We then present the SHOE language, which we feel has many of the features necessary to enable a semantic web, and describe an existing set of tools that make it easy to use the language.
    Date
    11. 5.2013 19:22:18
  6. Miles, A.: SKOS: requirements for standardization (2006) 0.04
    0.038238242 = product of:
      0.076476485 = sum of:
        0.025048172 = weight(_text_:retrieval in 5703) [ClassicSimilarity], result of:
          0.025048172 = score(doc=5703,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.20052543 = fieldWeight in 5703, 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=5703)
        0.025667597 = weight(_text_:use in 5703) [ClassicSimilarity], result of:
          0.025667597 = score(doc=5703,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 5703, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=5703)
        0.016396983 = weight(_text_:of in 5703) [ClassicSimilarity], result of:
          0.016396983 = score(doc=5703,freq=12.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.25392252 = fieldWeight in 5703, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=5703)
        0.009363732 = product of:
          0.018727465 = sum of:
            0.018727465 = weight(_text_:on in 5703) [ClassicSimilarity], result of:
              0.018727465 = score(doc=5703,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.20619515 = fieldWeight in 5703, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5703)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    This paper poses three questions regarding the planned development of the Simple Knowledge Organisation System (SKOS) towards W3C Recommendation status. Firstly, what is the fundamental purpose and therefore scope of SKOS? Secondly, which key software components depend on SKOS, and how do they interact? Thirdly, what is the wider technological and social context in which SKOS is likely to be applied and how might this influence design goals? Some tentative conclusions are drawn and in particular it is suggested that the scope of SKOS be restricted to the formal representation of controlled structured vocabularies intended for use within retrieval applications. However, the main purpose of this paper is to articulate the assumptions that have motivated the design of SKOS, so that these may be reviewed prior to a rigorous standardization initiative.
    Footnote
    Presented at the International Conference on Dublin Core and Metadata Applications in October 2006
  7. Smith, D.A.; Shadbolt, N.R.: FacetOntology : expressive descriptions of facets in the Semantic Web (2012) 0.04
    0.03724517 = product of:
      0.07449034 = sum of:
        0.029519552 = weight(_text_:retrieval in 2208) [ClassicSimilarity], result of:
          0.029519552 = score(doc=2208,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.23632148 = fieldWeight in 2208, 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=2208)
        0.021389665 = weight(_text_:use in 2208) [ClassicSimilarity], result of:
          0.021389665 = score(doc=2208,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.1691581 = fieldWeight in 2208, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2208)
        0.015778005 = weight(_text_:of in 2208) [ClassicSimilarity], result of:
          0.015778005 = score(doc=2208,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.24433708 = fieldWeight in 2208, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2208)
        0.007803111 = product of:
          0.015606222 = sum of:
            0.015606222 = weight(_text_:on in 2208) [ClassicSimilarity], result of:
              0.015606222 = score(doc=2208,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.1718293 = fieldWeight in 2208, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2208)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    The formal structure of the information on the Semantic Web lends itself to faceted browsing, an information retrieval method where users can filter results based on the values of properties ("facets"). Numerous faceted browsers have been created to browse RDF and Linked Data, but these systems use their own ontologies for defining how data is queried to populate their facets. Since the source data is the same format across these systems (specifically, RDF), we can unify the different methods of describing how to quer the underlying data, to enable compatibility across systems, and provide an extensible base ontology for future systems. To this end, we present FacetOntology, an ontology that defines how to query data to form a faceted browser, and a number of transformations and filters that can be applied to data before it is shown to users. FacetOntology overcomes limitations in the expressivity of existing work, by enabling the full expressivity of SPARQL when selecting data for facets. By applying a FacetOntology definition to data, a set of facets are specified, each with queries and filters to source RDF data, which enables faceted browsing systems to be created using that RDF data.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. Heery, R.; Wagner, H.: ¬A metadata registry for the Semantic Web (2002) 0.04
    0.037135556 = product of:
      0.099028155 = sum of:
        0.021174688 = weight(_text_:use in 1210) [ClassicSimilarity], result of:
          0.021174688 = score(doc=1210,freq=4.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.16745798 = fieldWeight in 1210, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1210)
        0.019910943 = weight(_text_:of in 1210) [ClassicSimilarity], result of:
          0.019910943 = score(doc=1210,freq=52.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.30833945 = fieldWeight in 1210, product of:
              7.2111025 = tf(freq=52.0), with freq of:
                52.0 = termFreq=52.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1210)
        0.057942525 = sum of:
          0.007724685 = weight(_text_:on in 1210) [ClassicSimilarity], result of:
            0.007724685 = score(doc=1210,freq=2.0), product of:
              0.090823986 = queryWeight, product of:
                2.199415 = idf(docFreq=13325, maxDocs=44218)
                0.041294612 = queryNorm
              0.08505116 = fieldWeight in 1210, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.199415 = idf(docFreq=13325, maxDocs=44218)
                0.02734375 = fieldNorm(doc=1210)
          0.05021784 = weight(_text_:line in 1210) [ClassicSimilarity], result of:
            0.05021784 = score(doc=1210,freq=2.0), product of:
              0.23157367 = queryWeight, product of:
                5.6078424 = idf(docFreq=440, maxDocs=44218)
                0.041294612 = queryNorm
              0.2168547 = fieldWeight in 1210, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                5.6078424 = idf(docFreq=440, maxDocs=44218)
                0.02734375 = fieldNorm(doc=1210)
      0.375 = coord(3/8)
    
    Abstract
    The Semantic Web activity is a W3C project whose goal is to enable a 'cooperative' Web where machines and humans can exchange electronic content that has clear-cut, unambiguous meaning. This vision is based on the automated sharing of metadata terms across Web applications. The declaration of schemas in metadata registries advance this vision by providing a common approach for the discovery, understanding, and exchange of semantics. However, many of the issues regarding registries are not clear, and ideas vary regarding their scope and purpose. Additionally, registry issues are often difficult to describe and comprehend without a working example. This article will explore the role of metadata registries and will describe three prototypes, written by the Dublin Core Metadata Initiative. The article will outline how the prototypes are being used to demonstrate and evaluate application scope, functional requirements, and technology solutions for metadata registries. Metadata schema registries are, in effect, databases of schemas that can trace an historical line back to shared data dictionaries and the registration process encouraged by the ISO/IEC 11179 community. New impetus for the development of registries has come with the development activities surrounding creation of the Semantic Web. The motivation for establishing registries arises from domain and standardization communities, and from the knowledge management community. Examples of current registry activity include:
    * Agencies maintaining directories of data elements in a domain area in accordance with ISO/IEC 11179 (This standard specifies good practice for data element definition as well as the registration process. Example implementations are the National Health Information Knowledgebase hosted by the Australian Institute of Health and Welfare and the Environmental Data Registry hosted by the US Environmental Protection Agency.); * The xml.org directory of the Extended Markup Language (XML) document specifications facilitating re-use of Document Type Definition (DTD), hosted by the Organization for the Advancement of Structured Information Standards (OASIS); * The MetaForm database of Dublin Core usage and mappings maintained at the State and University Library in Goettingen; * The Semantic Web Agreement Group Dictionary, a database of terms for the Semantic Web that can be referred to by humans and software agents; * LEXML, a multi-lingual and multi-jurisdictional RDF Dictionary for the legal world; * The SCHEMAS registry maintained by the European Commission funded SCHEMAS project, which indexes several metadata element sets as well as a large number of activity reports describing metadata related activities and initiatives. Metadata registries essentially provide an index of terms. Given the distributed nature of the Web, there are a number of ways this can be accomplished. For example, the registry could link to terms and definitions in schemas published by implementers and stored locally by the schema maintainer. Alternatively, the registry might harvest various metadata schemas from their maintainers. Registries provide 'added value' to users by indexing schemas relevant to a particular 'domain' or 'community of use' and by simplifying the navigation of terms by enabling multiple schemas to be accessed from one view. An important benefit of this approach is an increase in the reuse of existing terms, rather than users having to reinvent them. Merging schemas to one view leads to harmonization between applications and helps avoid duplication of effort. Additionally, the establishment of registries to index terms actively being used in local implementations facilitates the metadata standards activity by providing implementation experience transferable to the standards-making process.
  9. Kara, S.: ¬An ontology-based retrieval system using semantic indexing (2012) 0.04
    0.035053015 = product of:
      0.09347471 = sum of:
        0.050096344 = weight(_text_:retrieval in 3829) [ClassicSimilarity], result of:
          0.050096344 = score(doc=3829,freq=8.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.40105087 = fieldWeight in 3829, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=3829)
        0.025667597 = weight(_text_:use in 3829) [ClassicSimilarity], result of:
          0.025667597 = score(doc=3829,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 3829, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=3829)
        0.017710768 = weight(_text_:of in 3829) [ClassicSimilarity], result of:
          0.017710768 = score(doc=3829,freq=14.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2742677 = fieldWeight in 3829, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=3829)
      0.375 = coord(3/8)
    
    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.
    Content
    Thesis submitted to the Graduate School of Natural and Applied Sciences of Middle East Technical University in partial fulfilment of the requirements for the degree of Master of science in Computer Engineering (XII, 57 S.)
  10. Vocht, L. De: Exploring semantic relationships in the Web of Data : Semantische relaties verkennen in data op het web (2017) 0.03
    0.03356719 = product of:
      0.06713438 = sum of:
        0.010436738 = weight(_text_:retrieval in 4232) [ClassicSimilarity], result of:
          0.010436738 = score(doc=4232,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.08355226 = fieldWeight in 4232, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.01953125 = fieldNorm(doc=4232)
        0.030249555 = weight(_text_:use in 4232) [ClassicSimilarity], result of:
          0.030249555 = score(doc=4232,freq=16.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23922569 = fieldWeight in 4232, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.01953125 = fieldNorm(doc=4232)
        0.016501032 = weight(_text_:of in 4232) [ClassicSimilarity], result of:
          0.016501032 = score(doc=4232,freq=70.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2555338 = fieldWeight in 4232, product of:
              8.3666 = tf(freq=70.0), with freq of:
                70.0 = termFreq=70.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.01953125 = fieldNorm(doc=4232)
        0.009947053 = product of:
          0.019894106 = sum of:
            0.019894106 = weight(_text_:on in 4232) [ClassicSimilarity], result of:
              0.019894106 = score(doc=4232,freq=26.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.21904023 = fieldWeight in 4232, product of:
                  5.0990195 = tf(freq=26.0), with freq of:
                    26.0 = termFreq=26.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.01953125 = fieldNorm(doc=4232)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    After the launch of the World Wide Web, it became clear that searching documentson the Web would not be trivial. Well-known engines to search the web, like Google, focus on search in web documents using keywords. The documents are structured and indexed to ensure keywords match documents as accurately as possible. However, searching by keywords does not always suice. It is oen the case that users do not know exactly how to formulate the search query or which keywords guarantee retrieving the most relevant documents. Besides that, it occurs that users rather want to browse information than looking up something specific. It turned out that there is need for systems that enable more interactivity and facilitate the gradual refinement of search queries to explore the Web. Users expect more from the Web because the short keyword-based queries they pose during search, do not suffice for all cases. On top of that, the Web is changing structurally. The Web comprises, apart from a collection of documents, more and more linked data, pieces of information structured so they can be processed by machines. The consequently applied semantics allow users to exactly indicate machines their search intentions. This is made possible by describing data following controlled vocabularies, concept lists composed by experts, published uniquely identifiable on the Web. Even so, it is still not trivial to explore data on the Web. There is a large variety of vocabularies and various data sources use different terms to identify the same concepts.
    This PhD-thesis describes how to effectively explore linked data on the Web. The main focus is on scenarios where users want to discover relationships between resources rather than finding out more about something specific. Searching for a specific document or piece of information fits in the theoretical framework of information retrieval and is associated with exploratory search. Exploratory search goes beyond 'looking up something' when users are seeking more detailed understanding, further investigation or navigation of the initial search results. The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. Queries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research. Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data.
    The ideas behind exploratory search and querying linked data merge when it comes to the way knowledge is represented and indexed by machines - how data is structured and stored for optimal searchability. eries and information should be aligned to facilitate that searches also reveal connections between results. This implies that they take into account the same semantic entities, relevant at that moment. To realize this, we research three techniques that are evaluated one by one in an experimental set-up to assess how well they succeed in their goals. In the end, the techniques are applied to a practical use case that focuses on forming a bridge between the Web and the use of digital libraries in scientific research.
    Our first technique focuses on the interactive visualization of search results. Linked data resources can be brought in relation with each other at will. This leads to complex and diverse graphs structures. Our technique facilitates navigation and supports a workflow starting from a broad overview on the data and allows narrowing down until the desired level of detail to then broaden again. To validate the flow, two visualizations where implemented and presented to test-users. The users judged the usability of the visualizations, how the visualizations fit in the workflow and to which degree their features seemed useful for the exploration of linked data. There is a difference in the way users interact with resources, visually or textually, and how resources are represented for machines to be processed by algorithms. This difference complicates bridging the users' intents and machine executable queries. It is important to implement this 'translation' mechanism to impact the search as favorable as possible in terms of performance, complexity and accuracy. To do this, we explain a second technique, that supports such a bridging component. Our second technique is developed around three features that support the search process: looking up, relating and ranking resources. The main goal is to ensure that resources in the results are as precise and relevant as possible. During the evaluation of this technique, we did not only look at the precision of the search results but also investigated how the effectiveness of the search evolved while the user executed certain actions sequentially.
    When we speak about finding relationships between resources, it is necessary to dive deeper in the structure. The graph structure of linked data where the semantics give meaning to the relationships between resources enable the execution of pathfinding algorithms. The assigned weights and heuristics are base components of such algorithms and ultimately define (the order) which resources are included in a path. These paths explain indirect connections between resources. Our third technique proposes an algorithm that optimizes the choice of resources in terms of serendipity. Some optimizations guard the consistence of candidate-paths where the coherence of consecutive connections is maximized to avoid trivial and too arbitrary paths. The implementation uses the A* algorithm, the de-facto reference when it comes to heuristically optimized minimal cost paths. The effectiveness of paths was measured based on common automatic metrics and surveys where the users could indicate their preference for paths, generated each time in a different way. Finally, all our techniques are applied to a use case about publications in digital libraries where they are aligned with information about scientific conferences and researchers. The application to this use case is a practical example because the different aspects of exploratory search come together. In fact, the techniques also evolved from the experiences when implementing the use case. Practical details about the semantic model are explained and the implementation of the search system is clarified module by module. The evaluation positions the result, a prototype of a tool to explore scientific publications, researchers and conferences next to some important alternatives.
  11. Hogan, A.; Harth, A.; Umbrich, J.; Kinsella, S.; Polleres, A.; Decker, S.: Searching and browsing Linked Data with SWSE : the Semantic Web Search Engine (2011) 0.03
    0.032742057 = product of:
      0.065484114 = sum of:
        0.020873476 = weight(_text_:retrieval in 438) [ClassicSimilarity], result of:
          0.020873476 = score(doc=438,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.16710453 = fieldWeight in 438, 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=438)
        0.021389665 = weight(_text_:use in 438) [ClassicSimilarity], result of:
          0.021389665 = score(doc=438,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.1691581 = fieldWeight in 438, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0390625 = fieldNorm(doc=438)
        0.013664153 = weight(_text_:of in 438) [ClassicSimilarity], result of:
          0.013664153 = score(doc=438,freq=12.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.21160212 = fieldWeight in 438, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=438)
        0.00955682 = product of:
          0.01911364 = sum of:
            0.01911364 = weight(_text_:on in 438) [ClassicSimilarity], result of:
              0.01911364 = score(doc=438,freq=6.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.21044704 = fieldWeight in 438, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=438)
          0.5 = coord(1/2)
      0.5 = coord(4/8)
    
    Abstract
    In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web data - loosely also known as Linked Data - which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web - in terms of scale, unreliability, inconsistency and noise - are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a best-effort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.
  12. Sánchez, M.F.: Semantically enhanced Information Retrieval : an ontology-based approach (2006) 0.03
    0.030461663 = product of:
      0.0812311 = sum of:
        0.059039105 = weight(_text_:retrieval in 4327) [ClassicSimilarity], result of:
          0.059039105 = score(doc=4327,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.47264296 = fieldWeight in 4327, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.078125 = fieldNorm(doc=4327)
        0.011156735 = weight(_text_:of in 4327) [ClassicSimilarity], result of:
          0.011156735 = score(doc=4327,freq=2.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.17277241 = fieldWeight in 4327, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.078125 = fieldNorm(doc=4327)
        0.0110352645 = product of:
          0.022070529 = sum of:
            0.022070529 = weight(_text_:on in 4327) [ClassicSimilarity], result of:
              0.022070529 = score(doc=4327,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.24300331 = fieldWeight in 4327, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.078125 = fieldNorm(doc=4327)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Content
    Part I. Analyzing the state of the art - What is semantic search? Part II. The proposal - An ontology-based IR model - Semantic retrieval on the Web Part III. Extensions - Semantic knowledge gateway - Coping with knowledge incompleteness
  13. Shah, U.; Finin, T.; Joshi, A.; Cost, R.S.; Mayfield, J.: Information retrieval on the Semantic Web (2002) 0.03
    0.026950127 = product of:
      0.071867004 = sum of:
        0.050615493 = weight(_text_:retrieval in 696) [ClassicSimilarity], result of:
          0.050615493 = score(doc=696,freq=6.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.40520695 = fieldWeight in 696, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=696)
        0.013526822 = weight(_text_:of in 696) [ClassicSimilarity], result of:
          0.013526822 = score(doc=696,freq=6.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.20947541 = fieldWeight in 696, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=696)
        0.007724685 = product of:
          0.01544937 = sum of:
            0.01544937 = weight(_text_:on in 696) [ClassicSimilarity], result of:
              0.01544937 = score(doc=696,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.17010231 = fieldWeight in 696, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=696)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    We describe an apporach to retrieval of documents that consist of both free text and semantically enriched markup. In particular, we present the design and implementation prototype of a framework in which both documents and queries can be marked up with statements in the DAML+OIL semantic web language. These statement provide both structured and semi-structured information about the documents and their content. We claim that indexing text and semantic markup will significantly improve retrieval performance. Outr approach allows inferencing to be done over this information at several points: when a document is indexed,when a query is processed and when query results are evaluated.
  14. Mehler, A.; Waltinger, U.: Automatic enrichment of metadata (2009) 0.02
    0.021631874 = product of:
      0.057685 = sum of:
        0.033397563 = weight(_text_:retrieval in 4840) [ClassicSimilarity], result of:
          0.033397563 = score(doc=4840,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.26736724 = fieldWeight in 4840, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0625 = fieldNorm(doc=4840)
        0.0154592255 = weight(_text_:of in 4840) [ClassicSimilarity], result of:
          0.0154592255 = score(doc=4840,freq=6.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.23940048 = fieldWeight in 4840, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0625 = fieldNorm(doc=4840)
        0.008828212 = product of:
          0.017656423 = sum of:
            0.017656423 = weight(_text_:on in 4840) [ClassicSimilarity], result of:
              0.017656423 = score(doc=4840,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.19440265 = fieldWeight in 4840, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0625 = fieldNorm(doc=4840)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    In this talk we present a retrieval model based on social ontologies. More specifically, we utilize the Wikipedia category system in order to perform semantic searches. That is, textual input is used to build queries by means of which documents are retrieved which do not necessarily contain any query term but are semantically related to the input text by virtue of their content. We present a desktop which utilizes this search facility in a web-based environment - the so called eHumanities Desktop.
  15. Leskinen, P.; Hyvönen, E.: Extracting genealogical networks of linked data from biographical texts (2019) 0.02
    0.020674974 = product of:
      0.055133265 = sum of:
        0.029945528 = weight(_text_:use in 5798) [ClassicSimilarity], result of:
          0.029945528 = score(doc=5798,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 5798, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5798)
        0.017463053 = weight(_text_:of in 5798) [ClassicSimilarity], result of:
          0.017463053 = score(doc=5798,freq=10.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2704316 = fieldWeight in 5798, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5798)
        0.007724685 = product of:
          0.01544937 = sum of:
            0.01544937 = weight(_text_:on in 5798) [ClassicSimilarity], result of:
              0.01544937 = score(doc=5798,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.17010231 = fieldWeight in 5798, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=5798)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    This paper presents the idea and our work of extracting and reassembling a genealogical network automatically from a collection of biographies. The network can be used as a tool for network analysis of historical persons. The data has been published as Linked Data and as an interactive online service as part of the in-use data service and semantic portal BiographySampo - Finnish Biographies on the Semantic Web.
  16. Jacobs, I.: From chaos, order: W3C standard helps organize knowledge : SKOS Connects Diverse Knowledge Organization Systems to Linked Data (2009) 0.02
    0.020552069 = product of:
      0.054805517 = sum of:
        0.033480123 = weight(_text_:use in 3062) [ClassicSimilarity], result of:
          0.033480123 = score(doc=3062,freq=10.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.26477432 = fieldWeight in 3062, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.02734375 = fieldNorm(doc=3062)
        0.017463053 = weight(_text_:of in 3062) [ClassicSimilarity], result of:
          0.017463053 = score(doc=3062,freq=40.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2704316 = fieldWeight in 3062, product of:
              6.3245554 = tf(freq=40.0), with freq of:
                40.0 = termFreq=40.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.02734375 = fieldNorm(doc=3062)
        0.0038623426 = product of:
          0.007724685 = sum of:
            0.007724685 = weight(_text_:on in 3062) [ClassicSimilarity], result of:
              0.007724685 = score(doc=3062,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.08505116 = fieldWeight in 3062, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.02734375 = fieldNorm(doc=3062)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.
    Content
    SKOS Adapts to the Diversity of Knowledge Organization Systems A useful starting point for understanding the role of SKOS is the set of subject headings published by the US Library of Congress (LOC) for categorizing books, videos, and other library resources. These headings can be used to broaden or narrow queries for discovering resources. For instance, one can narrow a query about books on "Chinese literature" to "Chinese drama," or further still to "Chinese children's plays." Library of Congress subject headings have evolved within a community of practice over a period of decades. By now publishing these subject headings in SKOS, the Library of Congress has made them available to the linked data community, which benefits from a time-tested set of concepts to re-use in their own data. This re-use adds value ("the network effect") to the collection. When people all over the Web re-use the same LOC concept for "Chinese drama," or a concept from some other vocabulary linked to it, this creates many new routes to the discovery of information, and increases the chances that relevant items will be found. As an example of mapping one vocabulary to another, a combined effort from the STITCH, TELplus and MACS Projects provides links between LOC concepts and RAMEAU, a collection of French subject headings used by the Bibliothèque Nationale de France and other institutions. SKOS can be used for subject headings but also many other approaches to organizing knowledge. Because different communities are comfortable with different organization schemes, SKOS is designed to port diverse knowledge organization systems to the Web. "Active participation from the library and information science community in the development of SKOS over the past seven years has been key to ensuring that SKOS meets a variety of needs," said Thomas Baker, co-chair of the Semantic Web Deployment Working Group, which published SKOS. "One goal in creating SKOS was to provide new uses for well-established knowledge organization systems by providing a bridge to the linked data cloud." SKOS is part of the Semantic Web technology stack. Like the Web Ontology Language (OWL), SKOS can be used to define vocabularies. But the two technologies were designed to meet different needs. SKOS is a simple language with just a few features, tuned for sharing and linking knowledge organization systems such as thesauri and classification schemes. OWL offers a general and powerful framework for knowledge representation, where additional "rigor" can afford additional benefits (for instance, business rule processing). To get started with SKOS, see the SKOS Primer.
  17. OWL Web Ontology Language Overview (2004) 0.02
    0.020433892 = product of:
      0.05449038 = sum of:
        0.025667597 = weight(_text_:use in 4682) [ClassicSimilarity], result of:
          0.025667597 = score(doc=4682,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 4682, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=4682)
        0.022201622 = weight(_text_:of in 4682) [ClassicSimilarity], result of:
          0.022201622 = score(doc=4682,freq=22.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.34381276 = fieldWeight in 4682, product of:
              4.690416 = tf(freq=22.0), with freq of:
                22.0 = termFreq=22.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=4682)
        0.006621159 = product of:
          0.013242318 = sum of:
            0.013242318 = weight(_text_:on in 4682) [ClassicSimilarity], result of:
              0.013242318 = score(doc=4682,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.14580199 = fieldWeight in 4682, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4682)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    The OWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. OWL has three increasingly-expressive sublanguages: OWL Lite, OWL DL, and OWL Full. This document is written for readers who want a first impression of the capabilities of OWL. It provides an introduction to OWL by informally describing the features of each of the sublanguages of OWL. Some knowledge of RDF Schema is useful for understanding this document, but not essential. After this document, interested readers may turn to the OWL Guide for more detailed descriptions and extensive examples on the features of OWL. The normative formal definition of OWL can be found in the OWL Semantics and Abstract Syntax.
  18. OWL Web Ontology Language Guide (2004) 0.02
    0.020027824 = product of:
      0.05340753 = sum of:
        0.030249555 = weight(_text_:use in 4687) [ClassicSimilarity], result of:
          0.030249555 = score(doc=4687,freq=4.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23922569 = fieldWeight in 4687, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4687)
        0.017640345 = weight(_text_:of in 4687) [ClassicSimilarity], result of:
          0.017640345 = score(doc=4687,freq=20.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.27317715 = fieldWeight in 4687, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4687)
        0.0055176322 = product of:
          0.0110352645 = sum of:
            0.0110352645 = weight(_text_:on in 4687) [ClassicSimilarity], result of:
              0.0110352645 = score(doc=4687,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.121501654 = fieldWeight in 4687, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4687)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    The World Wide Web as it is currently constituted resembles a poorly mapped geography. Our insight into the documents and capabilities available are based on keyword searches, abetted by clever use of document connectivity and usage patterns. The sheer mass of this data is unmanageable without powerful tool support. In order to map this terrain more precisely, computational agents require machine-readable descriptions of the content and capabilities of Web accessible resources. These descriptions must be in addition to the human-readable versions of that information. The OWL Web Ontology Language is intended to provide a language that can be used to describe the classes and relations between them that are inherent in Web documents and applications. This document demonstrates the use of the OWL language to - formalize a domain by defining classes and properties of those classes, - define individuals and assert properties about them, and - reason about these classes and individuals to the degree permitted by the formal semantics of the OWL language. The sections are organized to present an incremental definition of a set of classes, properties and individuals, beginning with the fundamentals and proceeding to more complex language components.
  19. Christophides, V.; Plexousakis, D.; Scholl, M.; Tourtounis, S.: On labeling schemes for the Semantic Web (2003) 0.02
    0.019285616 = product of:
      0.05142831 = sum of:
        0.025667597 = weight(_text_:use in 3393) [ClassicSimilarity], result of:
          0.025667597 = score(doc=3393,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 3393, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=3393)
        0.016396983 = weight(_text_:of in 3393) [ClassicSimilarity], result of:
          0.016396983 = score(doc=3393,freq=12.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.25392252 = fieldWeight in 3393, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=3393)
        0.009363732 = product of:
          0.018727465 = sum of:
            0.018727465 = weight(_text_:on in 3393) [ClassicSimilarity], result of:
              0.018727465 = score(doc=3393,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.20619515 = fieldWeight in 3393, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3393)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    This paper focuses on the optimization of the navigation through voluminous subsumption hierarchies of topics employed by Portal Catalogs like Netscape Open Directory (ODP). We advocate for the use of labeling schemes for modeling these hierarchies in order to efficiently answer queries such as subsumption check, descendants, ancestors or nearest common ancestor, which usually require costly transitive closure computations. We first give a qualitative comparison of three main families of schemes, namely bit vector, prefix and interval based schemes. We then show that two labeling schemes are good candidates for an efficient implementation of label querying using standard relational DBMS, namely, the Dewey Prefix scheme [6] and an Interval scheme by Agrawal, Borgida and Jagadish [1]. We compare their storage and query evaluation performance for the 16 ODP hierarchies using the PostgreSQL engine.
  20. Menzel, C.: Knowledge representation, the World Wide Web, and the evolution of logic (2011) 0.02
    0.019208387 = product of:
      0.05122236 = sum of:
        0.025667597 = weight(_text_:use in 761) [ClassicSimilarity], result of:
          0.025667597 = score(doc=761,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.20298971 = fieldWeight in 761, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=761)
        0.018933605 = weight(_text_:of in 761) [ClassicSimilarity], result of:
          0.018933605 = score(doc=761,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2932045 = fieldWeight in 761, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=761)
        0.006621159 = product of:
          0.013242318 = sum of:
            0.013242318 = weight(_text_:on in 761) [ClassicSimilarity], result of:
              0.013242318 = score(doc=761,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.14580199 = fieldWeight in 761, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=761)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    In this paper, I have traced a series of evolutionary adaptations of FOL motivated entirely by its use by knowledge engineers to represent and share information on the Web culminating in the development of Common Logic. While the primary goal in this paper has been to document this evolution, it is arguable, I think that CL's syntactic and semantic egalitarianism better realizes the goal "topic neutrality" that a logic should ideally exemplify - understood, at least in part, as the idea that logic should as far as possible not itself embody any metaphysical presuppositions. Instead of retaining the traditional metaphysical divisions of FOL that reflect its Fregean origins, CL begins as it were with a single, metaphysically homogeneous domain in which, potentially, anything can play the traditional roles of object, property, relation, and function. Note that the effect of this is not to destroy traditional metaphysical divisions. Rather, it simply to refrain from building those divisions explicitly into one's logic; instead, such divisions are left to the user to introduce and enforce axiomatically in an explicit metaphysical theory.

Years

Types

  • a 23
  • n 10
  • x 2
  • r 1
  • More… Less…