Search (28 results, page 2 of 2)

0.0012307836 = product of:
  0.0067693098 = sum of:
    0.0046860883 = weight(_text_:a in 2908) [ClassicSimilarity], result of:
      0.0046860883 = score(doc=2908,freq=8.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = 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)
    0.0020832212 = weight(_text_:s in 2908) [ClassicSimilarity], result of:
      0.0020832212 = score(doc=2908,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.072074346 = fieldWeight in 2908, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.046875 = fieldNorm(doc=2908)
  0.18181819 = coord(2/11)

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.

Source

Knowledge organization. 43(2016) no.3, S.174-179

Type

a

0.001185225 = product of:
  0.006518737 = sum of:
    0.004782719 = weight(_text_:a in 2703) [ClassicSimilarity], result of:
      0.004782719 = score(doc=2703,freq=12.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = queryNorm
        0.15602624 = fieldWeight in 2703, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2703)
    0.0017360178 = weight(_text_:s in 2703) [ClassicSimilarity], result of:
      0.0017360178 = score(doc=2703,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.060061958 = fieldWeight in 2703, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2703)
  0.18181819 = coord(2/11)

Abstract

This paper discusses two inter-related themes: the retrieval potential of faceted thesauri and XML representations of fundamental facets. Initial findings are discussed from the ongoing 'FACET' project, in collaboration with the National Museum of Science and Industry. The work discussed seeks to take advantage of the structure afforded by faceted systems for multi-term queries and flexible matching, focusing in this paper an the Art and Architecture Thesaurus. A multi-term matching function yields ranked results with partial matches via semantic term expansion, based an a measure of distance over the semantic index space formed by thesaurus relationships. Our intention is to drive the system from general representations and a common query structure and interface. To this end, we are developing an XML representation based an work by the Classification Research Group an fundamental facets or categories. The XML representation maps categories to particular thesauri and hierarchies. The system interface, which is configured by the mapping, incorporates a thesaurus browser with navigation history together with a term search facility and drag and drop query builder.

Pages

S.191-197

Type

a

0.001185225 = product of:
  0.006518737 = sum of:
    0.004782719 = weight(_text_:a in 2895) [ClassicSimilarity], result of:
      0.004782719 = score(doc=2895,freq=12.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = queryNorm
        0.15602624 = fieldWeight in 2895, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2895)
    0.0017360178 = weight(_text_:s in 2895) [ClassicSimilarity], result of:
      0.0017360178 = score(doc=2895,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.060061958 = fieldWeight in 2895, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2895)
  0.18181819 = coord(2/11)

Abstract

The article presents a method for automatic semantic indexing of archaeological grey-literature reports using empirical (rule-based) Information Extraction techniques in combination with domain-specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word-Sense Disambiguation using hand-crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH. Relation Extraction (RE) performance benefits from a syntactic-based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word-Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion. The semantic indexing results demonstrate the capacity of rule-based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context-driven RE rules for the recognition of semantic relationships from phrases of unstructured text.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1138-1152

Type

a

0.0011834023 = product of:
  0.006508712 = sum of:
    0.0052934997 = weight(_text_:a in 2677) [ClassicSimilarity], result of:
      0.0052934997 = score(doc=2677,freq=30.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = queryNorm
        0.17268941 = fieldWeight in 2677, product of:
          5.477226 = tf(freq=30.0), with freq of:
            30.0 = termFreq=30.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2677)
    0.0012152124 = weight(_text_:s in 2677) [ClassicSimilarity], result of:
      0.0012152124 = score(doc=2677,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.04204337 = fieldWeight in 2677, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.02734375 = fieldNorm(doc=2677)
  0.18181819 = coord(2/11)

Abstract

This paper discusses research that employs methods from Natural Language Processing (NLP) in exploiting the intellectual resources of Knowledge Organization Systems (KOS), particularly in the retrieval of information. A technique for the disambiguation of homographs and nominal compounds in free text, where these are known ambiguous terms in the KOS itself, is described. The use of Roget's Thesaurus as an intermediary in the process is also reported. A short review of the relevant literature in the field is given. Design considerations, results and conclusions are presented from the implementation of a prototype system. The linguistic techniques are applied at two complementary levels, namely an a free text string used as an entry point to the KOS, and an the underlying controlled vocabulary itself.

Content

1. Introduction The need for research into the application of linguistic techniques in Information Retrieval (IR) in general, and a similar need in faceted Knowledge Organization Systems (KOS) has been indicated by various authors. Smeaton (1997) points out the inherent limitations of conventional approaches to IR based an "bags of words", mainly difficulties caused by lexical ambiguity in the words concerned, and goes an to suggest the possibility of using Natural Language Processing (NLP) in query formulation. Past experience with a faceted retrieval system highlighted the need for integrating the linguistic perspective in order to fully utilise the potential of a KOS (Tudhope et al." 2002). The present research seeks to address some of these needs in using NLP to improve the efficacy of KOS tools in query and retrieval systems. Syntactic parsing and part-of-speech tagging can substantially reduce lexical ambiguity through homograph disambiguation. Given the two strings "1 fable the motion" and "I put the motion an the fable", for instance, the parser used in this research clearly indicates that 'fable' in the first string is a verb, while 'table' in the second string is a noun, a distinction that would be missed in the "bag of words" approach. This syntactic disambiguation enables a more precise matching from free text to the controlled vocabulary of a KOS and vice versa. The use of a general linguistic resource, namely Roget's Thesaurus of English Words and Phrases (RTEWP), as an intermediary in this process, is investigated. The adaptation of the Link parser (Sleator & Temperley, 1993) to the purposes of the research is reported. The design and implementation of the early practical stages of the project are described, and the results of the initial experiments are presented and evaluated. Applications of the techniques developed are foreseen in the areas of query disambiguation, information retrieval and automatic indexing. In the first section of the paper a brief review of the literature and relevant current work in the field is presented. The second section includes reports an the development of algorithms, the construction of data sets and theoretical and experimental work undertaken to date. The third section evaluates the results obtained, and outlines directions for future research.

Pages

S.351-356

Type

a

0.0011045277 = product of:
  0.0060749026 = sum of:
    0.0046860883 = weight(_text_:a in 2320) [ClassicSimilarity], result of:
      0.0046860883 = score(doc=2320,freq=18.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = 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)
    0.0013888142 = weight(_text_:s in 2320) [ClassicSimilarity], result of:
      0.0013888142 = score(doc=2320,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.048049565 = fieldWeight in 2320, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.03125 = fieldNorm(doc=2320)
  0.18181819 = coord(2/11)

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.

Source

Journal of documentation. 71(2015) no.5, S.976-998

Type

a

0.001025653 = product of:
  0.005641091 = sum of:
    0.0039050733 = weight(_text_:a in 600) [ClassicSimilarity], result of:
      0.0039050733 = score(doc=600,freq=8.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = 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)
    0.0017360178 = weight(_text_:s in 600) [ClassicSimilarity], result of:
      0.0017360178 = score(doc=600,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.060061958 = fieldWeight in 600, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.0390625 = fieldNorm(doc=600)
  0.18181819 = coord(2/11)

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.

Source

Journal of documentation. 77(2021) no.4, S.926-945

Type

a

8.176949E-4 = product of:
  0.004497322 = sum of:
    0.0027613041 = weight(_text_:a in 5913) [ClassicSimilarity], result of:
      0.0027613041 = score(doc=5913,freq=4.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = 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)
    0.0017360178 = weight(_text_:s in 5913) [ClassicSimilarity], result of:
      0.0017360178 = score(doc=5913,freq=2.0), product of:
        0.028903782 = queryWeight, product of:
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.026584605 = queryNorm
        0.060061958 = fieldWeight in 5913, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.0872376 = idf(docFreq=40523, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5913)
  0.18181819 = coord(2/11)

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).

Source

New review of hypermedia and multimedia. 12(2006) no.1, S.3-9

Type

a

5.4997404E-4 = product of:
  0.006049714 = sum of:
    0.006049714 = weight(_text_:a in 1955) [ClassicSimilarity], result of:
      0.006049714 = score(doc=1955,freq=30.0), product of:
        0.030653298 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.026584605 = queryNorm
        0.19735932 = fieldWeight in 1955, product of:
          5.477226 = tf(freq=30.0), with freq of:
            30.0 = termFreq=30.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.03125 = fieldNorm(doc=1955)
  0.09090909 = coord(1/11)

Abstract

Dublin Core recommends controlled terminology for the subject of a resource. Knowledge organization systems (KOS), such as classifications, gazetteers, taxonomies and thesauri, provide controlled vocabularies that organize and structure concepts for indexing, classifying, browsing and search. For example, a thesaurus employs a set of standard semantic relationships (ISO 2788, ISO 5964), and major thesauri have a large entry vocabulary of terms considered equivalent for retrieval purposes. Many KOS have been made available for Web-based access. However, they are often not fully integrated into indexing and search systems and the full potential for networked and programmatic access remains untapped. The lack of standardized access and interchange formats impedes wider use of KOS resources. We developed a Web demonstrator (www.comp.glam.ac.uk/~FACET/webdemo/) for the FACET project (www.comp.glam.ac.uk/~facet/facetproject.html) that explored thesaurus-based query expansion with the Getty Art and Architecture Thesaurus. A Web demonstrator was implemented via Active Server Pages (ASP) with server-side scripting and compiled server-side components for database access, and cascading style sheets for presentation. The browser-based interactive interface permits dynamic control of query term expansion. However, being based on a custom thesaurus representation and API, the techniques cannot be applied directly to thesauri in other formats on the Web. General programmatic access requires commonly agreed protocols, for example, building on Web and Grid services. The development of common KOS representation formats and service protocols are closely linked. Linda Hill and colleagues argued in 2002 for a general KOS service protocol from which protocols for specific types of KOS can be derived. Thus, in the future, a combination of thesaurus and query protocols might permit a thesaurus to be used with a choice of search tools on various kinds of databases. Service-oriented architectures bring an opportunity for moving toward a clearer separation of interface components from the underlying data sources. In our view, basing distributed protocol services on the atomic elements of thesaurus data structures and relationships is not necessarily the best approach because client operations that require multiple client-server calls would carry too much overhead. This would limit the interfaces that could be offered by applications following such a protocol. Advanced interactive interfaces require protocols that group primitive thesaurus data elements (via their relationships) into composites to achieve reasonable response.

Type

a