Search (108 results, page 1 of 6)

  • × language_ss:"e"
  • × theme_ss:"Semantic Web"
  • × type_ss:"a"
  1. Veltman, K.H.: Syntactic and semantic interoperability : new approaches to knowledge and the Semantic Web (2001) 0.05 
    0.04832034 = product of:
  0.09664068 = sum of:
    0.0059903543 = weight(_text_:information in 3883) [ClassicSimilarity], result of:
      0.0059903543 = score(doc=3883,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.0775819 = fieldWeight in 3883, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=3883)
    0.061179362 = weight(_text_:united in 3883) [ClassicSimilarity], result of:
      0.061179362 = score(doc=3883,freq=2.0), product of:
        0.24675635 = queryWeight, product of:
          5.6101127 = idf(docFreq=439, maxDocs=44218)
          0.043984205 = queryNorm
        0.2479343 = fieldWeight in 3883, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.6101127 = idf(docFreq=439, maxDocs=44218)
          0.03125 = fieldNorm(doc=3883)
    0.029470965 = product of:
      0.05894193 = sum of:
        0.05894193 = weight(_text_:states in 3883) [ClassicSimilarity], result of:
          0.05894193 = score(doc=3883,freq=2.0), product of:
            0.24220218 = queryWeight, product of:
              5.506572 = idf(docFreq=487, maxDocs=44218)
              0.043984205 = queryNorm
            0.24335839 = fieldWeight in 3883, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.506572 = idf(docFreq=487, maxDocs=44218)
              0.03125 = fieldNorm(doc=3883)
      0.5 = coord(1/2)
  0.5 = coord(3/6)
    Abstract
    At VVWW-7 (Brisbane, 1997), Tim Berners-Lee outlined his vision of a global reasoning web. At VVWW- 8 (Toronto, May 1998), he developed this into a vision of a semantic web, where one Gould search not just for isolated words, but for meaning in the form of logically provable claims. In the past four years this vision has spread with amazing speed. The semantic web has been adopted by the European Commission as one of the important goals of the Sixth Framework Programme. In the United States it has become linked with the Defense Advanced Research Projects Agency (DARPA). While this quest to achieve a semantic web is new, the quest for meaning in language has a history that is almost as old as language itself. Accordingly this paper opens with a survey of the historical background. The contributions of the Dublin Core are reviewed briefly. To achieve a semantic web requires both syntactic and semantic interoperability. These challenges are outlined. A basic contention of this paper is that semantic interoperability requires much more than a simple agreement concerning the static meaning of a term. Different levels of agreement (local, regional, national and international) are involved and these levels have their own history. Hence, one of the larger challenges is to create new systems of knowledge organization, which identify and connect these different levels. With respect to meaning or semantics, early twentieth century pioneers such as Wüster were hopeful that it might be sufficient to limit oneself to isolated terms and words without reference to the larger grammatical context: to concept systems rather than to propositional logic. While a fascination with concept systems implicitly dominates many contemporary discussions, this paper suggests why this approach is not sufficient. The final section of this paper explores how an approach using propositional logic could lead to a new approach to universals and particulars. This points to a re-organization of knowledge, and opens the way for a vision of a semantic web with all the historical and cultural richness and complexity of language itself.
    Source
    New review of information networking. 7(2001) no.xx, S.xx-xx
  2. Guns, R.: Tracing the origins of the semantic web (2013) 0.03 
    0.028121524 = product of:
  0.08436457 = sum of:
    0.007487943 = weight(_text_:information in 1093) [ClassicSimilarity], result of:
      0.007487943 = score(doc=1093,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.09697737 = fieldWeight in 1093, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1093)
    0.076876625 = weight(_text_:networks in 1093) [ClassicSimilarity], result of:
      0.076876625 = score(doc=1093,freq=4.0), product of:
        0.20804176 = queryWeight, product of:
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.043984205 = queryNorm
        0.369525 = fieldWeight in 1093, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1093)
  0.33333334 = coord(2/6)
    Abstract
    The Semantic Web has been criticized for not being semantic. This article examines the questions of why and how the Web of Data, expressed in the Resource Description Framework (RDF), has come to be known as the Semantic Web. Contrary to previous papers, we deliberately take a descriptive stance and do not start from preconceived ideas about the nature of semantics. Instead, we mainly base our analysis on early design documents of the (Semantic) Web. The main determining factor is shown to be link typing, coupled with the influence of online metadata. Both factors already were present in early web standards and drafts. Our findings indicate that the Semantic Web is directly linked to older artificial intelligence work, despite occasional claims to the contrary. Because of link typing, the Semantic Web can be considered an example of a semantic network. Originally network representations of the meaning of natural language utterances, semantic networks have eventually come to refer to any networks with typed (usually directed) links. We discuss possible causes for this shift and suggest that it may be due to confounding paradigmatic and syntagmatic semantic relations.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.10, S.2173-2181
  3. Mayr, P.; Mutschke, P.; Petras, V.: Reducing semantic complexity in distributed digital libraries : Treatment of term vagueness and document re-ranking (2008) 0.02 
    0.02244316 = product of:
  0.06732948 = sum of:
    0.0129694985 = weight(_text_:information in 1909) [ClassicSimilarity], result of:
      0.0129694985 = score(doc=1909,freq=6.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.16796975 = fieldWeight in 1909, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1909)
    0.054359984 = weight(_text_:networks in 1909) [ClassicSimilarity], result of:
      0.054359984 = score(doc=1909,freq=2.0), product of:
        0.20804176 = queryWeight, product of:
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.043984205 = queryNorm
        0.26129362 = fieldWeight in 1909, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1909)
  0.33333334 = coord(2/6)
    Abstract
    Purpose - The general science portal "vascoda" merges structured, high-quality information collections from more than 40 providers on the basis of search engine technology (FAST) and a concept which treats semantic heterogeneity between different controlled vocabularies. First experiences with the portal show some weaknesses of this approach which come out in most metadata-driven Digital Libraries (DLs) or subject specific portals. The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value-added services (treatment of term vagueness and document re-ranking) that gain a certain quality in DLs if they are combined with heterogeneity components established in the project "Competence Center Modeling and Treatment of Semantic Heterogeneity". Design/methodology/approach - Two methods, which are derived from scientometrics and network analysis, will be implemented with the objective to re-rank result sets by the following structural properties: the ranking of the results by core journals (so-called Bradfordizing) and ranking by centrality of authors in co-authorship networks. Findings - The methods, which will be implemented, focus on the query and on the result side of a search and are designed to positively influence each other. Conceptually, they will improve the search quality and guarantee that the most relevant documents in result sets will be ranked higher. Originality/value - The central impact of the paper focuses on the integration of three structural value-adding methods, which aim at reducing the semantic complexity represented in distributed DLs at several stages in the information retrieval process: query construction, search and ranking and re-ranking.
    Theme
    Information Gateway
  4. Baker, T.; Sutton, S.A.: Linked data and the charm of weak semantics : Introduction: the strengths of weak semantics (2015) 0.02 
    0.021649845 = product of:
  0.064949535 = sum of:
    0.01058955 = weight(_text_:information in 2022) [ClassicSimilarity], result of:
      0.01058955 = score(doc=2022,freq=4.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.13714671 = fieldWeight in 2022, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2022)
    0.054359984 = weight(_text_:networks in 2022) [ClassicSimilarity], result of:
      0.054359984 = score(doc=2022,freq=2.0), product of:
        0.20804176 = queryWeight, product of:
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.043984205 = queryNorm
        0.26129362 = fieldWeight in 2022, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2022)
  0.33333334 = coord(2/6)
    Abstract
    Logic and precision are fundamental to ontologies underlying the semantic web and, by extension, to linked data. This special section focuses on the interaction of semantics, ontologies and linked data. The discussion presents the Simple Knowledge Organization Scheme (SKOS) as a less formal strategy for expressing concept hierarchies and associations and questions the value of deep domain ontologies in favor of simpler vocabularies that are more open to reuse, albeit risking illogical outcomes. RDF ontologies harbor another unexpected drawback. While structurally sound, they leave validation gaps permitting illogical uses, a problem being addressed by a W3C Working Group. Data models based on RDF graphs and properties may replace traditional library catalog models geared to predefined entities, with relationships between RDF classes providing the semantic connections. The BIBFRAME Initiative takes a different and streamlined approach to linking data, building rich networks of information resources rather than relying on a strict underlying structure and vocabulary. Taken together, the articles illustrate the trend toward a pragmatic approach to a Semantic Web, sacrificing some specificity for greater flexibility and partial interoperability.
    Source
    Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.10-12
  5. Papadakis, I. et al.: Highlighting timely information in libraries through social and semantic Web technologies (2016) 0.02 
    0.01699179 = product of:
  0.050975367 = sum of:
    0.0211791 = weight(_text_:information in 2090) [ClassicSimilarity], result of:
      0.0211791 = score(doc=2090,freq=4.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.27429342 = fieldWeight in 2090, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=2090)
    0.029796265 = product of:
      0.05959253 = sum of:
        0.05959253 = weight(_text_:22 in 2090) [ClassicSimilarity], result of:
          0.05959253 = score(doc=2090,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.38690117 = fieldWeight in 2090, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.078125 = fieldNorm(doc=2090)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Series
    Communications in computer and information science; 672
    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  6. Leskinen, P.; Hyvönen, E.: Extracting genealogical networks of linked data from biographical texts (2019) 0.01 
    0.012683997 = product of:
  0.07610398 = sum of:
    0.07610398 = weight(_text_:networks in 5798) [ClassicSimilarity], result of:
      0.07610398 = score(doc=5798,freq=2.0), product of:
        0.20804176 = queryWeight, product of:
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.043984205 = queryNorm
        0.36581108 = fieldWeight in 5798, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.72992 = idf(docFreq=1060, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5798)
  0.16666667 = coord(1/6)
  7. Heflin, J.; Hendler, J.: Semantic interoperability on the Web (2000) 0.01 
    0.010446835 = product of:
  0.031340506 = sum of:
    0.010483121 = weight(_text_:information in 759) [ClassicSimilarity], result of:
      0.010483121 = score(doc=759,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.13576832 = fieldWeight in 759, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=759)
    0.020857384 = product of:
      0.04171477 = sum of:
        0.04171477 = weight(_text_:22 in 759) [ClassicSimilarity], result of:
          0.04171477 = score(doc=759,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = 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)
  0.33333334 = coord(2/6)
    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
  8. Franklin, R.A.: Re-inventing subject access for the semantic web (2003) 0.01 
    0.00895443 = product of:
  0.026863288 = sum of:
    0.0089855315 = weight(_text_:information in 2556) [ClassicSimilarity], result of:
      0.0089855315 = score(doc=2556,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.116372846 = fieldWeight in 2556, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=2556)
    0.017877758 = product of:
      0.035755515 = sum of:
        0.035755515 = weight(_text_:22 in 2556) [ClassicSimilarity], result of:
          0.035755515 = score(doc=2556,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.23214069 = fieldWeight in 2556, 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=2556)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Date
    30.12.2008 18:22:46
    Source
    Online information review. 27(2003) no.2, S.94-101
  9. Hooland, S. van; Verborgh, R.; Wilde, M. De; Hercher, J.; Mannens, E.; Wa, R.Van de: Evaluating the success of vocabulary reconciliation for cultural heritage collections (2013) 0.01 
    0.00895443 = product of:
  0.026863288 = sum of:
    0.0089855315 = weight(_text_:information in 662) [ClassicSimilarity], result of:
      0.0089855315 = score(doc=662,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.116372846 = fieldWeight in 662, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=662)
    0.017877758 = product of:
      0.035755515 = sum of:
        0.035755515 = weight(_text_:22 in 662) [ClassicSimilarity], result of:
          0.035755515 = score(doc=662,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.23214069 = fieldWeight in 662, 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=662)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Date
    22. 3.2013 19:29:20
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.464-479
  10. Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.01 
    0.00895443 = product of:
  0.026863288 = sum of:
    0.0089855315 = weight(_text_:information in 2024) [ClassicSimilarity], result of:
      0.0089855315 = score(doc=2024,freq=2.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.116372846 = fieldWeight in 2024, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=2024)
    0.017877758 = product of:
      0.035755515 = sum of:
        0.035755515 = weight(_text_:22 in 2024) [ClassicSimilarity], result of:
          0.035755515 = score(doc=2024,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.23214069 = fieldWeight in 2024, 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=2024)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Source
    Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22
  11. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.01 
    0.008863939 = product of:
  0.026591817 = sum of:
    0.014673311 = weight(_text_:information in 1626) [ClassicSimilarity], result of:
      0.014673311 = score(doc=1626,freq=12.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.19003606 = fieldWeight in 1626, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=1626)
    0.011918506 = product of:
      0.023837011 = sum of:
        0.023837011 = weight(_text_:22 in 1626) [ClassicSimilarity], result of:
          0.023837011 = score(doc=1626,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.15476047 = fieldWeight in 1626, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=1626)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    Purpose - The growing volumes of semantic data available in the web result in the need for handling the information overload phenomenon. The potential of this amount of data is enormous but in most cases it is very difficult for users to visualize, explore and use this data, especially for lay-users without experience with Semantic Web technologies. The paper aims to discuss these issues. Design/methodology/approach - The Visual Information-Seeking Mantra "Overview first, zoom and filter, then details-on-demand" proposed by Shneiderman describes how data should be presented in different stages to achieve an effective exploration. The overview is the first user task when dealing with a data set. The objective is that the user is capable of getting an idea about the overall structure of the data set. Different information architecture (IA) components supporting the overview tasks have been developed, so they are automatically generated from semantic data, and evaluated with end-users. Findings - The chosen IA components are well known to web users, as they are present in most web pages: navigation bars, site maps and site indexes. The authors complement them with Treemaps, a visualization technique for displaying hierarchical data. These components have been developed following an iterative User-Centered Design methodology. Evaluations with end-users have shown that they get easily used to them despite the fact that they are generated automatically from structured data, without requiring knowledge about the underlying semantic technologies, and that the different overview components complement each other as they focus on different information search needs. Originality/value - Obtaining semantic data sets overviews cannot be easily done with the current semantic web browsers. Overviews become difficult to achieve with large heterogeneous data sets, which is typical in the Semantic Web, because traditional IA techniques do not easily scale to large data sets. There is little or no support to obtain overview information quickly and easily at the beginning of the exploration of a new data set. This can be a serious limitation when exploring a data set for the first time, especially for lay-users. The proposal is to reuse and adapt existing IA components to provide this overview to users and show that they can be generated automatically from the thesaurus and ontologies that structure semantic data while providing a comparable user experience to traditional web sites.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.5, S.519-536
  12. Subirats, I.; Prasad, A.R.D.; Keizer, J.; Bagdanov, A.: Implementation of rich metadata formats and demantic tools using DSpace (2008) 0.01 
    0.0074313683 = product of:
  0.022294104 = sum of:
    0.010375599 = weight(_text_:information in 2656) [ClassicSimilarity], result of:
      0.010375599 = score(doc=2656,freq=6.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.1343758 = fieldWeight in 2656, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=2656)
    0.011918506 = product of:
      0.023837011 = sum of:
        0.023837011 = weight(_text_:22 in 2656) [ClassicSimilarity], result of:
          0.023837011 = score(doc=2656,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.15476047 = fieldWeight in 2656, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=2656)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    This poster explores the customization of DSpace to allow the use of the AGRIS Application Profile metadata standard and the AGROVOC thesaurus. The objective is the adaptation of DSpace, through the least invasive code changes either in the form of plug-ins or add-ons, to the specific needs of the Agricultural Sciences and Technology community. Metadata standards such as AGRIS AP, and Knowledge Organization Systems such as the AGROVOC thesaurus, provide mechanisms for sharing information in a standardized manner by recommending the use of common semantics and interoperable syntax (Subirats et al., 2007). AGRIS AP was created to enhance the description, exchange and subsequent retrieval of agricultural Document-like Information Objects (DLIOs). It is a metadata schema which draws from Metadata standards such as Dublin Core (DC), the Australian Government Locator Service Metadata (AGLS) and the Agricultural Metadata Element Set (AgMES) namespaces. It allows sharing of information across dispersed bibliographic systems (FAO, 2005). AGROVOC68 is a multilingual structured thesaurus covering agricultural and related domains. Its main role is to standardize the indexing process in order to make searching simpler and more efficient. AGROVOC is developed by FAO (Lauser et al., 2006). The customization of the DSpace is taking place in several phases. First, the AGRIS AP metadata schema was mapped onto the metadata DSpace model, with several enhancements implemented to support AGRIS AP elements. Next, AGROVOC will be integrated as a controlled vocabulary accessed through a local SKOS or OWL file. Eventually the system will be configurable to access AGROVOC through local files or remotely via webservices. Finally, spell checking and tooltips will be incorporated in the user interface to support metadata editing. Adapting DSpace to support AGRIS AP and annotation using the semantically-rich AGROVOC thesaurus transform DSpace into a powerful, domain-specific system for annotation and exchange of bibliographic metadata in the agricultural domain.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  13. Shoffner, M.; Greenberg, J.; Kramer-Duffield, J.; Woodbury, D.: Web 2.0 semantic systems : collaborative learning in science (2008) 0.01 
    0.0067967153 = product of:
  0.020390145 = sum of:
    0.008471641 = weight(_text_:information in 2661) [ClassicSimilarity], result of:
      0.008471641 = score(doc=2661,freq=4.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.10971737 = fieldWeight in 2661, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=2661)
    0.011918506 = product of:
      0.023837011 = sum of:
        0.023837011 = weight(_text_:22 in 2661) [ClassicSimilarity], result of:
          0.023837011 = score(doc=2661,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.15476047 = fieldWeight in 2661, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=2661)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    The basic goal of education within a discipline is to transform a novice into an expert. This entails moving the novice toward the "semantic space" that the expert inhabits-the space of concepts, meanings, vocabularies, and other intellectual constructs that comprise the discipline. Metadata is significant to this goal in digitally mediated education environments. Encoding the experts' semantic space not only enables the sharing of semantics among discipline scientists, but also creates an environment that bridges the semantic gap between the common vocabulary of the novice and the granular descriptive language of the seasoned scientist (Greenberg, et al, 2005). Developments underlying the Semantic Web, where vocabularies are formalized in the Web Ontology Language (OWL), and Web 2.0 approaches of user-generated folksonomies provide an infrastructure for linking vocabulary systems and promoting group learning via metadata literacy. Group learning is a pedagogical approach to teaching that harnesses the phenomenon of "collective intelligence" to increase learning by means of collaboration. Learning a new semantic system can be daunting for a novice, and yet it is integral to advance one's knowledge in a discipline and retain interest. These ideas are key to the "BOT 2.0: Botany through Web 2.0, the Memex and Social Learning" project (Bot 2.0).72 Bot 2.0 is a collaboration involving the North Carolina Botanical Garden, the UNC SILS Metadata Research center, and the Renaissance Computing Institute (RENCI). Bot 2.0 presents a curriculum utilizing a memex as a way for students to link and share digital information, working asynchronously in an environment beyond the traditional classroom. Our conception of a memex is not a centralized black box but rather a flexible, distributed framework that uses the most salient and easiest-to-use collaborative platforms (e.g., Facebook, Flickr, wiki and blog technology) for personal information management. By meeting students "where they live" digitally, we hope to attract students to the study of botanical science. A key aspect is to teach students scientific terminology and about the value of metadata, an inherent function in several of the technologies and in the instructional approach we are utilizing. This poster will report on a study examining the value of both folksonomies and taxonomies for post-secondary college students learning plant identification. Our data is drawn from a curriculum involving a virtual independent learning portion and a "BotCamp" weekend at UNC, where students work with digital plan specimens that they have captured. Results provide some insight into the importance of collaboration and shared vocabulary for gaining confidence and for student progression from novice to expert in botany.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  14. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.01 
    0.0067967153 = product of:
  0.020390145 = sum of:
    0.008471641 = weight(_text_:information in 1634) [ClassicSimilarity], result of:
      0.008471641 = score(doc=1634,freq=4.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.10971737 = fieldWeight in 1634, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=1634)
    0.011918506 = product of:
      0.023837011 = sum of:
        0.023837011 = weight(_text_:22 in 1634) [ClassicSimilarity], result of:
          0.023837011 = score(doc=1634,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.15476047 = fieldWeight in 1634, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=1634)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.5, S.494-518
  15. Shaw, R.; Buckland, M.: Open identification and linking of the four Ws (2008) 0.01 
    0.005947126 = product of:
  0.017841378 = sum of:
    0.0074126855 = weight(_text_:information in 2665) [ClassicSimilarity], result of:
      0.0074126855 = score(doc=2665,freq=4.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.0960027 = fieldWeight in 2665, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2665)
    0.010428692 = product of:
      0.020857384 = sum of:
        0.020857384 = weight(_text_:22 in 2665) [ClassicSimilarity], result of:
          0.020857384 = score(doc=2665,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.1354154 = fieldWeight in 2665, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2665)
      0.5 = coord(1/2)
  0.33333334 = coord(2/6)
    Abstract
    Platforms for social computing connect users via shared references to people with whom they have relationships, events attended, places lived in or traveled to, and topics such as favorite books or movies. Since free text is insufficient for expressing such references precisely and unambiguously, many social computing platforms coin identifiers for topics, places, events, and people and provide interfaces for finding and selecting these identifiers from controlled lists. Using these interfaces, users collaboratively construct a web of links among entities. This model needn't be limited to social networking sites. Understanding an item in a digital library or museum requires context: information about the topics, places, events, and people to which the item is related. Students, journalists and investigators traditionally discover this kind of context by asking "the four Ws": what, where, when and who. The DCMI Kernel Metadata Community has recognized the four Ws as fundamental elements of descriptions (Kunze & Turner, 2007). Making better use of metadata to answer these questions via links to appropriate contextual resources has been our focus in a series of research projects over the past few years. Currently we are building a system for enabling readers of any text to relate any topic, place, event or person mentioned in the text to the best explanatory resources available. This system is being developed with two different corpora: a diverse variety of biographical texts characterized by very rich and dense mentions of people, events, places and activities, and a large collection of newly-scanned books, journals and manuscripts relating to Irish culture and history. Like a social computing platform, our system consists of tools for referring to topics, places, events or people, disambiguating these references by linking them to unique identifiers, and using the disambiguated references to provide useful information in context and to link to related resources. Yet current social computing platforms, while usually amenable to importing and exporting data, tend to mint proprietary identifiers and expect links to be traversed using their own interfaces. We take a different approach, using identifiers from both established and emerging naming authorities, representing relationships using standardized metadata vocabularies, and publishing those representations using standard protocols so that links can be stored and traversed anywhere. Central to our strategy is to move from appearances in a text to naming authorities to the the construction of links for searching or querying trusted resources. Using identifiers from naming authorities, rather than literal values (as in the DCMI Kernel) or keys from a proprietary database, makes it more likely that links constructed using our system will continue to be useful in the future. WorldCat Identities URIs (http://worldcat.org/identities/) linked to Library of Congress and Deutsche Nationalbibliothek authority files for persons and organizations and Geonames (http://geonames.org/) URIs for places are stable identifiers attached to a wealth of useful metadata. Yet no naming authority can be totally comprehensive, so our system can be extended to use new sources of identifiers as needed. For example, we are experimenting with using Freebase (http://freebase.com/) URIs to identify historical events, for which no established naming authority currently exists. Stable identifiers (URIs), standardized hyperlinked data formats (XML), and uniform publishing protocols (HTTP) are key ingredients of the web's open architecture. Our system provides an example of how this open architecture can be exploited to build flexible and useful tools for connecting resources via shared references to topics, places, events, and people.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  16. Zhang, L.: Linking information through function (2014) 0.00 
    0.0042358204 = product of:
  0.025414921 = sum of:
    0.025414921 = weight(_text_:information in 1526) [ClassicSimilarity], result of:
      0.025414921 = score(doc=1526,freq=16.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.3291521 = fieldWeight in 1526, product of:
          4.0 = tf(freq=16.0), with freq of:
            16.0 = termFreq=16.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=1526)
  0.16666667 = coord(1/6)
    Abstract
    How information resources can be meaningfully related has been addressed in contexts from bibliographic entries to hyperlinks and, more recently, linked data. The genre structure and relationships among genre structure constituents shed new light on organizing information by purpose or function. This study examines the relationships among a set of functional units previously constructed in a taxonomy, each of which is a chunk of information embedded in a document and is distinct in terms of its communicative function. Through a card-sort study, relationships among functional units were identified with regard to their occurrence and function. The findings suggest that a group of functional units can be identified, collocated, and navigated by particular relationships. Understanding how functional units are related to each other is significant in linking information pieces in documents to support finding, aggregating, and navigating information in a distributed information environment.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.11, S.2293-2305
  17. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.00 
    0.0039728354 = product of:
  0.023837011 = sum of:
    0.023837011 = product of:
      0.047674023 = sum of:
        0.047674023 = weight(_text_:22 in 3376) [ClassicSimilarity], result of:
          0.047674023 = score(doc=3376,freq=2.0), product of:
            0.1540252 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043984205 = queryNorm
            0.30952093 = fieldWeight in 3376, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0625 = fieldNorm(doc=3376)
      0.5 = coord(1/2)
  0.16666667 = coord(1/6)
    Date
    31. 7.2010 16:58:22
  18. Scheir, P.; Pammer, V.; Lindstaedt, S.N.: Information retrieval on the Semantic Web : does it exist? (2007) 0.00 
    0.0039068284 = product of:
  0.02344097 = sum of:
    0.02344097 = weight(_text_:information in 4329) [ClassicSimilarity], result of:
      0.02344097 = score(doc=4329,freq=10.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.3035872 = fieldWeight in 4329, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=4329)
  0.16666667 = coord(1/6)
    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.
    Source
    Lernen - Wissen - Adaption : workshop proceedings / LWA 2007, Halle, September 2007. Martin Luther University Halle-Wittenberg, Institute for Informatics, Databases and Information Systems. Hrsg.: Alexander Hinneburg
  19. Davies, J.; Weeks, R.; Krohn, U.: QuizRDF: search technology for the Semantic Web (2004) 0.00 
    0.003599755 = product of:
  0.02159853 = sum of:
    0.02159853 = weight(_text_:information in 4406) [ClassicSimilarity], result of:
      0.02159853 = score(doc=4406,freq=26.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.2797255 = fieldWeight in 4406, product of:
          5.0990195 = tf(freq=26.0), with freq of:
            26.0 = termFreq=26.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.03125 = fieldNorm(doc=4406)
  0.16666667 = coord(1/6)
    Abstract
    Important information is often scattered across Web and/or intranet resources. Traditional search engines return ranked retrieval lists that offer little or no information on the semantic relationships among documents. Knowledge workers spend a substantial amount of their time browsing and reading to find out how documents are related to one another and where each falls into the overall structure of the problem domain. Yet only when knowledge workers begin to locate the similarities and differences among pieces of information do they move into an essential part of their work: building relationships to create new knowledge. Information retrieval traditionally focuses on the relationship between a given query (or user profile) and the information store. On the other hand, exploitation of interrelationships between selected pieces of information (which can be facilitated by the use of ontologies) can put otherwise isolated information into a meaningful context. The implicit structures so revealed help users use and manage information more efficiently. Knowledge management tools are needed that integrate the resources dispersed across Web resources into a coherent corpus of interrelated information. Previous research in information integration has largely focused on integrating heterogeneous databases and knowledge bases, which represent information in a highly structured way, often by means of formal languages. In contrast, the Web consists to a large extent of unstructured or semi-structured natural language texts. As we have seen, ontologies offer an alternative way to cope with heterogeneous representations of Web resources. The domain model implicit in an ontology can be taken as a unifying structure for giving information a common representation and semantics. Once such a unifying structure exists, it can be exploited to improve browsing and retrieval performance in information access tools. QuizRDF is an example of such a tool.
  20. Krause, J.: Shell Model, Semantic Web and Web Information Retrieval (2006) 0.00 
    0.0035298502 = product of:
  0.0211791 = sum of:
    0.0211791 = weight(_text_:information in 6061) [ClassicSimilarity], result of:
      0.0211791 = score(doc=6061,freq=16.0), product of:
        0.0772133 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.043984205 = queryNorm
        0.27429342 = fieldWeight in 6061, 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=6061)
  0.16666667 = coord(1/6)
    Abstract
    The middle of the 1990s are coined by the increased enthusiasm for the possibilities of the WWW, which has only recently deviated - at least in relation to scientific information - for the differentiated measuring of its advantages and disadvantages. Web Information Retrieval originated as a specialized discipline with great commercial significance (for an overview see Lewandowski 2005). Besides the new technological structure that enables the indexing and searching (in seconds) of unimaginable amounts of data worldwide, new assessment processes for the ranking of search results are being developed, which use the link structures of the Web. They are the main innovation with respect to the traditional "mother discipline" of Information Retrieval. From the beginning, link structures of Web pages are applied to commercial search engines in a wide array of variations. From the perspective of scientific information, link topology based approaches were in essence trying to solve a self-created problem: on the one hand, it quickly became clear that the openness of the Web led to an up-tonow unknown increase in available information, but this also caused the quality of the Web pages searched to become a problem - and with it the relevance of the results. The gatekeeper function of traditional information providers, which narrows down every user query to focus on high-quality sources was lacking. Therefore, the recognition of the "authoritativeness" of the Web pages by general search engines such as Google was one of the most important factors for their success.
    Source
    Information und Sprache: Beiträge zu Informationswissenschaft, Computerlinguistik, Bibliothekswesen und verwandten Fächern. Festschrift für Harald H. Zimmermann. Herausgegeben von Ilse Harms, Heinz-Dirk Luckhardt und Hans W. Giessen

Authors

Years

Types

Themes