Search (28 results, page 2 of 2)

0.0020296127 = product of:
  0.0040592253 = sum of:
    0.0040592253 = product of:
      0.008118451 = sum of:
        0.008118451 = weight(_text_:a in 2908) [ClassicSimilarity], result of:
          0.008118451 = score(doc=2908,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15287387 = fieldWeight in 2908, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=2908)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The recent ISKO-UK conference considered the question of whether the traditional thesaurus has any place in modern information retrieval. This note is intended to continue in the spirit of that good-natured debate, arguing that there is indeed a role today and highlighting some recent work showing the continued relevance of the thesaurus, particularly in the linked data area. Key functionality that a thesaurus makes possible is discussed. A brief outline is provided of prominent work hat employs thesauri in three key areas of infrastructure underpinning advanced retrieval functionality today: metadata enrichment,vocabulary mapping and web services.

Type

a

0.0020296127 = product of:
  0.0040592253 = sum of:
    0.0040592253 = product of:
      0.008118451 = sum of:
        0.008118451 = weight(_text_:a in 2320) [ClassicSimilarity], result of:
          0.008118451 = score(doc=2320,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15287387 = fieldWeight in 2320, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.03125 = fieldNorm(doc=2320)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The purpose of this paper is to describe a new approach to a well-known problem for digital libraries, how to search across multiple unrelated libraries with a single query. Design/methodology/approach - The approach involves creating new Dewey Decimal Classification terms and numbers from existing Dublin Core records. In total, 263,550 records were harvested from three digital libraries. Weighted key terms were extracted from the title, description and subject fields of each record. Ranked DDC classes were automatically generated from these key terms by considering DDC hierarchies via a series of filtering and aggregation stages. A mean reciprocal ranking evaluation compared a sample of 49 generated classes against DDC classes created by a trained librarian for the same records. Findings - The best results combined weighted key terms from the title, description and subject fields. Performance declines with increased specificity of DDC level. The results compare favorably with similar studies. Research limitations/implications - The metadata harvest required manual intervention and the evaluation was resource intensive. Future research will look at evaluation methodologies that take account of issues of consistency and ecological validity. Practical implications - The method does not require training data and is easily scalable. The pipeline can be customized for individual use cases, for example, recall or precision enhancing. Social implications - The approach can provide centralized access to information from multiple domains currently provided by individual digital libraries. Originality/value - The approach addresses metadata normalization in the context of web resources. The automatic classification approach accounts for matches within hierarchies, aggregating lower level matches to broader parents and thus approximates the practices of a human cataloger.

Type

a

0.0018909799 = product of:
  0.0037819599 = sum of:
    0.0037819599 = product of:
      0.0075639198 = sum of:
        0.0075639198 = weight(_text_:a in 2215) [ClassicSimilarity], result of:
          0.0075639198 = score(doc=2215,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.14243183 = fieldWeight in 2215, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2215)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The purpose of this paper is to explore query expansion via conceptual distance in thesaurus indexed collections Design/methodology/approach - An extract of the National Museum of Science and Industry's collections database, indexed with the Getty Art and Architecture Thesaurus (AAT), was the dataset for the research. The system architecture and algorithms for semantic closeness and the matching function are outlined. Standalone and web interfaces are described and formative qualitative user studies are discussed. One user session is discussed in detail, together with a scenario based on a related public inquiry. Findings are set in context of the literature on thesaurus-based query expansion. This paper discusses the potential of query expansion techniques using the semantic relationships in a faceted thesaurus. Findings - Thesaurus-assisted retrieval systems have potential for multi-concept descriptors, permitting very precise queries and indexing. However, indexer and searcher may differ in terminology judgments and there may not be any exactly matching results. The integration of semantic closeness in the matching function permits ranked results for multi-concept queries in thesaurus-indexed applications. An in-memory representation of the thesaurus semantic network allows a combination of automatic and interactive control of expansion and control of expansion on individual query terms. Originality/value - The application of semantic expansion to browsing may be useful in interface options where thesaurus structure is hidden.

Type

a

0.0018909799 = product of:
  0.0037819599 = sum of:
    0.0037819599 = product of:
      0.0075639198 = sum of:
        0.0075639198 = weight(_text_:a in 2918) [ClassicSimilarity], result of:
          0.0075639198 = score(doc=2918,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.14243183 = fieldWeight in 2918, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2918)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.

Type

a

0.0018909799 = product of:
  0.0037819599 = sum of:
    0.0037819599 = product of:
      0.0075639198 = sum of:
        0.0075639198 = weight(_text_:a in 3179) [ClassicSimilarity], result of:
          0.0075639198 = score(doc=3179,freq=10.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.14243183 = fieldWeight in 3179, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3179)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

There are many advantages for Digital Libraries in indexing with classifications or thesauri, but some current disincentive in the lack of flexible retrieval tools that deal with compound descriptors. This paper discusses a matching function for compound descriptors, or multi-concept subject headings, that does not rely an exact matching but incorporates term expansion via thesaurus semantic relationships to produce ranked results that take account of missing and partially matching terms. The matching function is based an a measure of semantic closeness between terms, which has the potential to help with recall problems. The work reported is part of the ongoing FACET project in collaboration with the National Museum of Science and Industry and its collections database. The architecture of the prototype system and its Interface are outlined. The matching problem for compound descriptors is reviewed and the FACET implementation described. Results are discussed from scenarios using the faceted Getty Art and Architecture Thesaurus. We argue that automatic traversal of thesaurus relationships can augment the user's browsing possibilities. The techniques can be applied both to unstructured multi-concept subject headings and potentially to more syntactically structured strings. The notion of a focus term is used by the matching function to model AAT modified descriptors (noun phrases). The relevance of the approach to precoordinated indexing and matching faceted strings is discussed.

Type

a

0.0016913437 = product of:
  0.0033826875 = sum of:
    0.0033826875 = product of:
      0.006765375 = sum of:
        0.006765375 = weight(_text_:a in 600) [ClassicSimilarity], result of:
          0.006765375 = score(doc=600,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.12739488 = fieldWeight in 600, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=600)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose The Integrative Levels Classification (ILC) is a comprehensive "freely faceted" knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation. Design/methodology/approach The design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool. Findings The ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed. Originality/value Complex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship - specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.

Type

a

0.0016571716 = product of:
  0.0033143433 = sum of:
    0.0033143433 = product of:
      0.0066286866 = sum of:
        0.0066286866 = weight(_text_:a in 3948) [ClassicSimilarity], result of:
          0.0066286866 = score(doc=3948,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.12482099 = fieldWeight in 3948, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.03125 = fieldNorm(doc=3948)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - This paper sets out to discuss the use of information extraction (IE), a natural language-processing (NLP) technique to assist "rich" semantic indexing of diverse archaeological text resources. The focus of the research is to direct a semantic-aware "rich" indexing of diverse natural language resources with properties capable of satisfying information retrieval from online publications and datasets associated with the Semantic Technologies for Archaeological Resources (STAR) project. Design/methodology/approach - The paper proposes use of the English Heritage extension (CRM-EH) of the standard core ontology in cultural heritage, CIDOC CRM, and exploitation of domain thesauri resources for driving and enhancing an Ontology-Oriented Information Extraction process. The process of semantic indexing is based on a rule-based Information Extraction technique, which is facilitated by the General Architecture of Text Engineering (GATE) toolkit and expressed by Java Annotation Pattern Engine (JAPE) rules. Findings - Initial results suggest that the combination of information extraction with knowledge resources and standard conceptual models is capable of supporting semantic-aware term indexing. Additional efforts are required for further exploitation of the technique and adoption of formal evaluation methods for assessing the performance of the method in measurable terms. Originality/value - The value of the paper lies in the semantic indexing of 535 unpublished online documents often referred to as "Grey Literature", from the Archaeological Data Service OASIS corpus (Online AccesS to the Index of archaeological investigationS), with respect to the CRM ontological concepts E49.Time Appellation and P19.Physical Object.

Type

a

0.0011959607 = product of:
  0.0023919214 = sum of:
    0.0023919214 = product of:
      0.0047838427 = sum of:
        0.0047838427 = weight(_text_:a in 5913) [ClassicSimilarity], result of:
          0.0047838427 = score(doc=5913,freq=4.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.090081796 = fieldWeight in 5913, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5913)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

In a very real sense, this special issue on Knowledge Organization Systems and Services is concerned with new applications, new contexts and new twists of old themes and problems. We are concerned with diverse attempts to apply the outcomes of much work over the years in artificial subject languages and their intellectual structures to facilitate access to digital information in various settings. This issue has its origins in NKOS workshops, held over the last two years in Bath, Vienna, Madrid and Denver, although the majority of contributions resulted from an open call for papers, disseminated in October 2005. NKOS (http://nkos.slis.kent.edu/) is an informal network whose general aim is to enable knowledge organization systems (KOS) to act as networked information services (both machine-to-machine and human facing), supporting the description and retrieval of information resources on the Internet. Since 1997, there has been an NKOS workshop each year, at either the JCDL or ECDL conference (2005 saw an NKOS workshop at both conferences and also at Dublin Core). Previous NKOS-related special issues have appeared in the online Journal of Digital Information in 2001 and 2004 (Hill and Koch 2001, Tudhope and Koch 2004).

Type

a