Search (23 results, page 1 of 2)

  • × type_ss:"el"
  • × theme_ss:"Konzeption und Anwendung des Prinzips Thesaurus"
  1. Qin, J.; Paling, S.: Converting a controlled vocabulary into an ontology : the case of GEM (2001) 0.01
    0.012340388 = product of:
      0.037021164 = sum of:
        0.037021164 = product of:
          0.07404233 = sum of:
            0.07404233 = weight(_text_:22 in 3895) [ClassicSimilarity], result of:
              0.07404233 = score(doc=3895,freq=2.0), product of:
                0.15947726 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045541126 = queryNorm
                0.46428138 = fieldWeight in 3895, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.09375 = fieldNorm(doc=3895)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Date
    24. 8.2005 19:20:22
  2. Doerr, M.: Semantic problems of thesaurus mapping (2001) 0.01
    0.011087399 = product of:
      0.033262197 = sum of:
        0.033262197 = weight(_text_:to in 5902) [ClassicSimilarity], result of:
          0.033262197 = score(doc=5902,freq=32.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.40173632 = fieldWeight in 5902, product of:
              5.656854 = tf(freq=32.0), with freq of:
                32.0 = termFreq=32.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5902)
      0.33333334 = coord(1/3)
    
    Abstract
    With networked information access to heterogeneous data sources, the problem of terminology provision and interoperability of controlled vocabulary schemes such as thesauri becomes increasingly urgent. Solutions are needed to improve the performance of full-text retrieval systems and to guide the design of controlled terminology schemes for use in structured data, including metadata. Thesauri are created in different languages, with different scope and points of view and at different levels of abstraction and detail, to accomodate access to a specific group of collections. In any wider search accessing distributed collections, the user would like to start with familiar terminology and let the system find out the correspondences to other terminologies in order to retrieve equivalent results from all addressed collections. This paper investigates possible semantic differences that may hinder the unambiguous mapping and transition from one thesaurus to another. It focusses on the differences of meaning of terms and their relations as intended by their creators for indexing and querying a specific collection, in contrast to methods investigating the statistical relevance of terms for objects in a collection. It develops a notion of optimal mapping, paying particular attention to the intellectual quality of mappings between terms from different vocabularies and to problems of polysemy. Proposals are made to limit the vagueness introduced by the transition from one vocabulary to another. The paper shows ways in which thesaurus creators can improve their methodology to meet the challenges of networked access of distributed collections created under varying conditions. For system implementers, the discussion will lead to a better understanding of the complexity of the problem
  3. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.01
    0.010283656 = product of:
      0.03085097 = sum of:
        0.03085097 = product of:
          0.06170194 = sum of:
            0.06170194 = weight(_text_:22 in 539) [ClassicSimilarity], result of:
              0.06170194 = score(doc=539,freq=2.0), product of:
                0.15947726 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045541126 = queryNorm
                0.38690117 = fieldWeight in 539, 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=539)
          0.5 = coord(1/2)
      0.33333334 = coord(1/3)
    
    Date
    26.12.2011 13:22:07
  4. Assem, M. van; Gangemi, A.; Schreiber, G.: Conversion of WordNet to a standard RDF/OWL representation (2006) 0.01
    0.0099786585 = product of:
      0.029935975 = sum of:
        0.029935975 = weight(_text_:to in 4641) [ClassicSimilarity], result of:
          0.029935975 = score(doc=4641,freq=18.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.36156267 = fieldWeight in 4641, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.046875 = fieldNorm(doc=4641)
      0.33333334 = coord(1/3)
    
    Abstract
    This paper presents an overview of the work in progress at the W3C to produce a standard conversion of WordNet to the RDF/OWL representation language in use in the SemanticWeb community. Such a standard representation is useful to provide application developers a high-quality resource and to promote interoperability. Important requirements in this conversion process are that it should be complete and should stay close to WordNet's conceptual model. The paper explains the steps taken to produce the conversion and details design decisions such as the composition of the class hierarchy and properties, the addition of suitable OWL semantics and the chosen format of the URIs. Additional topics include a strategy to incorporate OWL and RDFS semantics in one schema such that both RDF(S) infrastructure and OWL infrastructure can interpret the information correctly, problems encountered in understanding the Prolog source files and the description of the two versions that are provided (Basic and Full) to accommodate different usages of WordNet.
  5. Assem, M. van; Malaisé, V.; Miles, A.; Schreiber, G.: ¬A method to convert thesauri to SKOS (2006) 0.01
    0.00940797 = product of:
      0.02822391 = sum of:
        0.02822391 = weight(_text_:to in 4642) [ClassicSimilarity], result of:
          0.02822391 = score(doc=4642,freq=16.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.34088457 = fieldWeight in 4642, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.046875 = fieldNorm(doc=4642)
      0.33333334 = coord(1/3)
    
    Abstract
    Thesauri can be useful resources for indexing and retrieval on the Semantic Web, but often they are not published in RDF/OWL. To convert thesauri to RDF for use in Semantic Web applications and to ensure the quality and utility of the conversion a structured method is required. Moreover, if different thesauri are to be interoperable without complicated mappings, a standard schema for thesauri is required. This paper presents a method for conversion of thesauri to the SKOS RDF/OWL schema, which is a proposal for such a standard under development by W3Cs Semantic Web Best Practices Working Group. We apply the method to three thesauri: IPSV, GTAA and MeSH. With these case studies we evaluate our method and the applicability of SKOS for representing thesauri.
  6. Lee, M.; Baillie, S.; Dell'Oro, J.: TML: a Thesaural Markpup Language (200?) 0.01
    0.00880035 = product of:
      0.026401049 = sum of:
        0.026401049 = weight(_text_:to in 1622) [ClassicSimilarity], result of:
          0.026401049 = score(doc=1622,freq=14.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.3188683 = fieldWeight in 1622, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.046875 = fieldNorm(doc=1622)
      0.33333334 = coord(1/3)
    
    Abstract
    Thesauri are used to provide controlled vocabularies for resource classification. Their use can greatly assist document discovery because thesauri man date a consistent shared terminology for describing documents. A particular thesauras classifies documents according to an information community's needs. As a result, there are many different thesaural schemas. This has led to a proliferation of schema-specific thesaural systems. In our research, we exploit schematic regularities to design a generic thesaural ontology and specfiy it as a markup language. The language provides a common representational framework in which to encode the idiosyncrasies of specific thesauri. This approach has several advantages: it offers consistent syntax and semantics in which to express thesauri; it allows general purpose thesaural applications to leverage many thesauri; and it supports a single thesaural user interface by which information communities can consistently organise, score and retrieve electronic documents.
  7. Quick Guide to Publishing a Thesaurus on the Semantic Web (2008) 0.01
    0.008677262 = product of:
      0.026031785 = sum of:
        0.026031785 = weight(_text_:to in 4656) [ClassicSimilarity], result of:
          0.026031785 = score(doc=4656,freq=10.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.3144084 = fieldWeight in 4656, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4656)
      0.33333334 = coord(1/3)
    
    Abstract
    This document describes in brief how to express the content and structure of a thesaurus, and metadata about a thesaurus, in RDF. Using RDF allows data to be linked to and/or merged with other RDF data by semantic web applications. The Semantic Web, which is based on the Resource Description Framework (RDF), provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.
  8. Hill, L.: New Protocols for Gazetteer and Thesaurus Services (2002) 0.01
    0.008297049 = product of:
      0.024891147 = sum of:
        0.024891147 = weight(_text_:to in 1206) [ClassicSimilarity], result of:
          0.024891147 = score(doc=1206,freq=28.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.3006319 = fieldWeight in 1206, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.03125 = fieldNorm(doc=1206)
      0.33333334 = coord(1/3)
    
    Abstract
    The Alexandria Digital Library Project announces the online publication of two protocols to support querying and response interactions using distributed services: one for gazetteers and one for thesauri. These protocols have been developed for our own purposes and also to support the general interoperability of gazetteers and thesauri on the web. See <http://www.alexandria.ucsb.edu/~gjanee/gazetteer/> and <http://www.alexandria.ucsb.edu/~gjanee/thesaurus/>. For the gazetteer protocol, we have provided a page of test forms that can be used to experiment with the operational functions of the protocol in accessing two gazetteers: the ADL Gazetteer and the ESRI Gazetteer (ESRI has participated in the development of the gazetteer protocol). We are in the process of developing a thesaurus server and a simple client to demonstrate the use of the thesaurus protocol. We are soliciting comments on both protocols. Please remember that we are seeking protocols that are essentially "simple" and easy to implement and that support basic operations - they should not duplicate all of the functions of specialized gazetteer and thesaurus interfaces. We continue to discuss ways of handling various issues and to further develop the protocols. For the thesaurus protocol, outstanding issues include the treatment of multilingual thesauri and the degree to which the language attribute should be supported; whether the Scope Note element should be changed to a repeatable Note element; the best way to handle the hierarchical report for multi-hierarchies where portions of the hierarchy are repeated; and whether support for searching by term identifiers is redundant and unnecessary given that the terms themselves are unique within a thesaurus. For the gazetteer protocol, we continue to work on validation of query and report XML documents and on implementing the part of the protocol designed to support the submission of new entries to a gazetteer. We would like to encourage open discussion of these protocols through the NKOS discussion list (see the NKOS webpage at <http://nkos.slis.kent.edu/>) and the CGGR-L discussion list that focuses on gazetteer development (see ADL Gazetteer Development page at <http://www.alexandria.ucsb.edu/gazetteer>).
  9. Dextre Clarke, S.G.; Will, L.D.; Cochard, N.: ¬The BS8723 thesaurus data model and exchange format, and its relationship to SKOS (2008) 0.01
    0.0077611795 = product of:
      0.023283537 = sum of:
        0.023283537 = weight(_text_:to in 6051) [ClassicSimilarity], result of:
          0.023283537 = score(doc=6051,freq=2.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.28121543 = fieldWeight in 6051, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.109375 = fieldNorm(doc=6051)
      0.33333334 = coord(1/3)
    
  10. Will, L.D.: Publications on thesaurus construction and use : including some references to facet analysis, taxonomies, ontologies, topic maps and related issues (2005) 0.01
    0.0077611795 = product of:
      0.023283537 = sum of:
        0.023283537 = weight(_text_:to in 3192) [ClassicSimilarity], result of:
          0.023283537 = score(doc=3192,freq=2.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.28121543 = fieldWeight in 3192, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.109375 = fieldNorm(doc=3192)
      0.33333334 = coord(1/3)
    
  11. Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004) 0.01
    0.0077611795 = product of:
      0.023283537 = sum of:
        0.023283537 = weight(_text_:to in 4644) [ClassicSimilarity], result of:
          0.023283537 = score(doc=4644,freq=8.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.28121543 = fieldWeight in 4644, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4644)
      0.33333334 = coord(1/3)
    
    Abstract
    This paper describes a method for converting existing thesauri and related resources from their native format to RDF(S) and OWL. The method identifies four steps in the conversion process. In each step, decisions have to be taken with respect to the syntax or semantics of the resulting representation. Each step is supported through a number of guidelines. The method is illustrated through conversions of two large thesauri: MeSH and WordNet.
  12. Fischer, D.H.: Converting a thesaurus to OWL : Notes on the paper "The National Cancer Institute's Thesaurus and Ontology" (2004) 0.01
    0.0069958316 = product of:
      0.020987494 = sum of:
        0.020987494 = weight(_text_:to in 2362) [ClassicSimilarity], result of:
          0.020987494 = score(doc=2362,freq=26.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.25348413 = fieldWeight in 2362, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2362)
      0.33333334 = coord(1/3)
    
    Abstract
    The paper analysed here is a kind of position paper. In order to get a better under-standing of the reported work I used the retrieval interface of the thesaurus, the so-called NCI DTS Browser accessible via the Web3, and I perused the cited OWL file4 with numerous "Find" and "Find next" string searches. In addition the file was im-ported into Protégé 2000, Release 2.0, with OWL Plugin 1.0 and Racer Plugin 1.7.14. At the end of the paper's introduction the authors say: "In the following sections, this paper will describe the terminology development process at NCI, and the issues associated with converting a description logic based nomenclature to a semantically rich OWL ontology." While I will not deal with the first part, i.e. the terminology development process at NCI, I do not see the thesaurus as a description logic based nomenclature, or its cur-rent state and conversion already result in a "rich" OWL ontology. What does "rich" mean here? According to my view there is a great quantity of concepts and links but a very poor description logic structure which enables inferences. And what does the fol-lowing really mean, which is said a few lines previously: "Although editors have defined a number of named ontologic relations to support the description-logic based structure of the Thesaurus, additional relation-ships are considered for inclusion as required to support dependent applications."
    According to my findings several relations available in the thesaurus query interface as "roles", are not used, i.e. there are not yet any assertions with them. And those which are used do not contribute to complete concept definitions of concepts which represent thesaurus main entries. In other words: The authors claim to already have a "description logic based nomenclature", where there is not yet one which deserves that title by being much more than a thesaurus with strict subsumption and additional inheritable semantic links. In the last section of the paper the authors say: "The most time consuming process in this conversion was making a careful analysis of the Thesaurus to understand the best way to translate it into OWL." "For other conversions, these same types of distinctions and decisions must be made. The expressive power of a proprietary encoding can vary widely from that in OWL or RDF. Understanding the original semantics and engineering a solution that most closely duplicates it is critical for creating a useful and accu-rate ontology." My question is: What decisions were made and are they exemplary, can they be rec-ommended as "the best way"? I raise strong doubts with respect to that, and I miss more profound discussions of the issues at stake. The following notes are dedicated to a critical description and assessment of the results of that conversion activity. They are written in a tutorial style more or less addressing students, but myself being a learner especially in the field of medical knowledge representation I do not speak "ex cathedra".
  13. Jing, Y.; Croft, W.B.: ¬An association thesaurus for information retrieval (199?) 0.01
    0.006721379 = product of:
      0.020164136 = sum of:
        0.020164136 = weight(_text_:to in 4494) [ClassicSimilarity], result of:
          0.020164136 = score(doc=4494,freq=6.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.24353972 = fieldWeight in 4494, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4494)
      0.33333334 = coord(1/3)
    
    Abstract
    Although commonly used in both commercial and experimental information retrieval systems, thesauri have not demonstrated consistent benefits for retrieval performance, and it is difficult to construct a thesaurus automatically for large text databases. In this paper, an approach, called PhraseFinder, is proposed to construct collection-dependent association thesauri automatically using large full-text document collections. The association thesaurus can be accessed through natural language queries in INQUERY, an information retrieval system based on the probabilistic inference network. Experiments are conducted in INQUERY to evaluate different types of association thesauri, and thesauri constructed for a variety of collections
  14. Assem, M. van: Converting and integrating vocabularies for the Semantic Web (2010) 0.01
    0.006652439 = product of:
      0.019957317 = sum of:
        0.019957317 = weight(_text_:to in 4639) [ClassicSimilarity], result of:
          0.019957317 = score(doc=4639,freq=18.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.24104178 = fieldWeight in 4639, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.03125 = fieldNorm(doc=4639)
      0.33333334 = coord(1/3)
    
    Abstract
    This thesis focuses on conversion of vocabularies for representation and integration of collections on the Semantic Web. A secondary focus is how to represent metadata schemas (RDF Schemas representing metadata element sets) such that they interoperate with vocabularies. The primary domain in which we operate is that of cultural heritage collections. The background worldview in which a solution is sought is that of the Semantic Web research paradigmwith its associated theories, methods, tools and use cases. In other words, we assume the SemanticWeb is in principle able to provide the context to realize interoperable collections. Interoperability is dependent on the interplay between representations and the applications that use them. We mean applications in the widest sense, such as "search" and "annotation". These applications or tasks are often present in software applications, such as the E-Culture application. It is therefore necessary that applications requirements on the vocabulary representation are met. This leads us to formulate the following problem statement: HOW CAN EXISTING VOCABULARIES BE MADE AVAILABLE TO SEMANTIC WEB APPLICATIONS?
    We refine the problem statement into three research questions. The first two focus on the problem of conversion of a vocabulary to a Semantic Web representation from its original format. Conversion of a vocabulary to a representation in a Semantic Web language is necessary to make the vocabulary available to SemanticWeb applications. In the last question we focus on integration of collection metadata schemas in a way that allows for vocabulary representations as produced by our methods. Academisch proefschrift ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, Dutch Research School for Information and Knowledge Systems.
  15. ALA / Subcommittee on Subject Relationships/Reference Structures: Final Report to the ALCTS/CCS Subject Analysis Committee (1997) 0.01
    0.00643523 = product of:
      0.01930569 = sum of:
        0.01930569 = weight(_text_:to in 1800) [ClassicSimilarity], result of:
          0.01930569 = score(doc=1800,freq=22.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.23317151 = fieldWeight in 1800, product of:
              4.690416 = tf(freq=22.0), with freq of:
                22.0 = termFreq=22.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1800)
      0.33333334 = coord(1/3)
    
    Abstract
    The SAC Subcommittee on Subject Relationships/Reference Structures was authorized at the 1995 Midwinter Meeting and appointed shortly before Annual Conference. Its creation was one result of a discussion of how (and why) to promote the display and use of broader-term subject heading references, and its charge reads as follows: To investigate: (1) the kinds of relationships that exist between subjects, the display of which are likely to be useful to catalog users; (2) how these relationships are or could be recorded in authorities and classification formats; (3) options for how these relationships should be presented to users of online and print catalogs, indexes, lists, etc. By the summer 1996 Annual Conference, make some recommendations to SAC about how to disseminate the information and/or implement changes. At that time assess the need for additional time to investigate these issues. The Subcommittee's work on each of the imperatives in the charge was summarized in a report issued at the 1996 Annual Conference (Appendix A). Highlights of this work included the development of a taxonomy of 165 subject relationships; a demonstration that, using existing MARC coding, catalog systems could be programmed to generate references they do not currently support; and an examination of reference displays in several CD-ROM database products. Since that time, work has continued on identifying term relationships and display options; on tracking research, discussion, and implementation of subject relationships in information systems; and on compiling a list of further research needs.
    Content
    Enthält: Appendix A: Subcommittee on Subject Relationships/Reference Structures - REPORT TO THE ALCTS/CCS SUBJECT ANALYSIS COMMITTEE - July 1996 Appendix B (part 1): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (alphabetical display) (Separat in: http://web2.ala.org/ala/alctscontent/CCS/committees/subjectanalysis/subjectrelations/msrscu2.pdf) Appendix B (part 2): Taxonomy of Subject Relationships. Compiled by Dee Michel with the assistance of Pat Kuhr - June 1996 draft (hierarchical display) Appendix C: Checklist of Candidate Subject Relationships for Information Retrieval. Compiled by Dee Michel, Pat Kuhr, and Jane Greenberg; edited by Greg Wool - June 1997 Appendix D: Review of Reference Displays in Selected CD-ROM Abstracts and Indexes by Harriette Hemmasi and Steven Riel Appendix E: Analysis of Relationships in Six LC Subject Authority Records by Harriette Hemmasi and Gary Strawn Appendix F: Report of a Preliminary Survey of Subject Referencing in OPACs by Gregory Wool Appendix G: LC Subject Referencing in OPACs--Why Bother? by Gregory Wool Appendix H: Research Needs on Subject Relationships and Reference Structures in Information Access compiled by Jane Greenberg and Steven Riel with contributions from Dee Michel and others edited by Gregory Wool Appendix I: Bibliography on Subject Relationships compiled mostly by Dee Michel with additional contributions from Jane Greenberg, Steven Riel, and Gregory Wool
  16. Eckert, K: ¬The ICE-map visualization (2011) 0.01
    0.00627198 = product of:
      0.018815938 = sum of:
        0.018815938 = weight(_text_:to in 4743) [ClassicSimilarity], result of:
          0.018815938 = score(doc=4743,freq=4.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.22725637 = fieldWeight in 4743, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0625 = fieldNorm(doc=4743)
      0.33333334 = coord(1/3)
    
    Abstract
    In this paper, we describe in detail the Information Content Evaluation Map (ICE-Map Visualization, formerly referred to as IC Difference Analysis). The ICE-Map Visualization is a visual data mining approach for all kinds of concept hierarchies that uses statistics about the concept usage to help a user in the evaluation and maintenance of the hierarchy. It consists of a statistical framework that employs the the notion of information content from information theory, as well as a visualization of the hierarchy and the result of the statistical analysis by means of a treemap.
  17. Martínez-González, M.M.; Alvite-Díez, M.L.: Thesauri and Semantic Web : discussion of the evolution of thesauri toward their integration with the Semantic Web (2019) 0.01
    0.0061980444 = product of:
      0.018594133 = sum of:
        0.018594133 = weight(_text_:to in 5997) [ClassicSimilarity], result of:
          0.018594133 = score(doc=5997,freq=10.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.22457743 = fieldWeight in 5997, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5997)
      0.33333334 = coord(1/3)
    
    Abstract
    Thesauri are Knowledge Organization Systems (KOS), that arise from the consensus of wide communities. They have been in use for many years and are regularly updated. Whereas in the past thesauri were designed for information professionals for indexing and searching, today there is a demand for conceptual vocabularies that enable inferencing by machines. The development of the Semantic Web has brought a new opportunity for thesauri, but thesauri also face the challenge of proving that they add value to it. The evolution of thesauri toward their integration with the Semantic Web is examined. Elements and structures in the thesaurus standard, ISO 25964, and SKOS (Simple Knowledge Organization System), the Semantic Web standard for representing KOS, are reviewed and compared. Moreover, the integrity rules of thesauri are contrasted with the axioms of SKOS. How SKOS has been applied to represent some real thesauri is taken into account. Three thesauri are chosen for this aim: AGROVOC, EuroVoc and the UNESCO Thesaurus. Based on the results of this comparison and analysis, the benefits that Semantic Web technologies offer to thesauri, how thesauri can contribute to the Semantic Web, and the challenges that would help to improve their integration with the Semantic Web are discussed.
  18. Michel, D.: Taxonomy of Subject Relationships (1997) 0.01
    0.0055436995 = product of:
      0.016631098 = sum of:
        0.016631098 = weight(_text_:to in 5346) [ClassicSimilarity], result of:
          0.016631098 = score(doc=5346,freq=2.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.20086816 = fieldWeight in 5346, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.078125 = fieldNorm(doc=5346)
      0.33333334 = coord(1/3)
    
    Abstract
    Teil von: Final Report to the ALCTS/CCS Subject Analysis Committee. June 1997 (http://web2.ala.org/ala/alctscontent/CCS/committees/subjectanalysis/subjectrelations/finalreport.cfm).
  19. Kless, D.: From a thesaurus standard to a general knowledge organization standard?! (2007) 0.01
    0.0055436995 = product of:
      0.016631098 = sum of:
        0.016631098 = weight(_text_:to in 528) [ClassicSimilarity], result of:
          0.016631098 = score(doc=528,freq=2.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.20086816 = fieldWeight in 528, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.078125 = fieldNorm(doc=528)
      0.33333334 = coord(1/3)
    
  20. Thesaurus software (2001) 0.01
    0.005487982 = product of:
      0.016463947 = sum of:
        0.016463947 = weight(_text_:to in 6773) [ClassicSimilarity], result of:
          0.016463947 = score(doc=6773,freq=4.0), product of:
            0.08279609 = queryWeight, product of:
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.045541126 = queryNorm
            0.19884932 = fieldWeight in 6773, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.818051 = idf(docFreq=19512, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6773)
      0.33333334 = coord(1/3)
    
    Abstract
    Members offer comments and suggest resources on programs for creating, maintaining, and publishing thesauri. Formerly a tool for writers and indexers, the thesaurus has taken on a new role as an essential component of the corporate information infrastructure. Many people are using word processor or database programs to create and maintain thesauri, while others are using specialized tools that perform consistency checks and offer special reporting capabilities. Some also use thesaurus modules integrated into another application, such as web publishing, content management, or e-commerce. This article includes material comes from our own experience, email responses from members, and comments from participants in our seminars and roundtables. There's also an introduction to thesauri in a corporate information management system