Search (35 results, page 1 of 2)

0.030438973 = product of:
  0.091316916 = sum of:
    0.091316916 = sum of:
      0.020087399 = weight(_text_:of in 100) [ClassicSimilarity], result of:
        0.020087399 = score(doc=100,freq=4.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.2932045 = fieldWeight in 100, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.09375 = fieldNorm(doc=100)
      0.07122952 = weight(_text_:22 in 100) [ClassicSimilarity], result of:
        0.07122952 = score(doc=100,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.46428138 = fieldWeight in 100, 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=100)
  0.33333334 = coord(1/3)

Date

22. 9.2007 15:41:14

0.019357719 = product of:
  0.058073156 = sum of:
    0.058073156 = sum of:
      0.022458395 = weight(_text_:of in 1347) [ClassicSimilarity], result of:
        0.022458395 = score(doc=1347,freq=20.0), product of:
          0.06850986 = queryWeight, product of:
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.043811057 = queryNorm
          0.32781258 = fieldWeight in 1347, product of:
            4.472136 = tf(freq=20.0), with freq of:
              20.0 = termFreq=20.0
            1.5637573 = idf(docFreq=25162, maxDocs=44218)
            0.046875 = fieldNorm(doc=1347)
      0.03561476 = weight(_text_:22 in 1347) [ClassicSimilarity], result of:
        0.03561476 = score(doc=1347,freq=2.0), product of:
          0.15341885 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.043811057 = queryNorm
          0.23214069 = fieldWeight in 1347, 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=1347)
  0.33333334 = coord(1/3)

Abstract

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Date

22. 8.2014 17:12:54

Source

Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1901-1916

0.009892989 = product of:
  0.029678967 = sum of:
    0.029678967 = product of:
      0.059357934 = sum of:
        0.059357934 = weight(_text_:22 in 539) [ClassicSimilarity], result of:
          0.059357934 = score(doc=539,freq=2.0), product of:
            0.15341885 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.043811057 = 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

0.0045201816 = product of:
  0.013560544 = sum of:
    0.013560544 = product of:
      0.027121088 = sum of:
        0.027121088 = weight(_text_:of in 1520) [ClassicSimilarity], result of:
          0.027121088 = score(doc=1520,freq=42.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.39587128 = fieldWeight in 1520, product of:
              6.4807405 = tf(freq=42.0), with freq of:
                42.0 = termFreq=42.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1520)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This paper discusses issues concerning the augmentation of thesaurus relationships, in light of new application possibilities for retrieval. We first discuss a case study that explored the retrieval potential of an augmented set of thesaurus relationships by specialising standard relationships into richer subtypes, in particular hierarchical geographical containment and the associative relationship. We then locate this work in a broader context by reviewing various attempts to build taxonomies of thesaurus relationships, and conclude by discussing the feasibility of hierarchically augmenting the core set of thesaurus relationships, particularly the associative relationship. We discuss the possibility of enriching the specification and semantics of Related Term (RT relationships), while maintaining compatibility with traditional thesauri via a limited hierarchical extension of the associative (and hierarchical) relationships. This would be facilitated by distinguishing the type of term from the (sub)type of relationship and explicitly specifying semantic categories for terms following a faceted approach. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but also the problem of uncontrolled expansion of query term sets. Results presented in this paper suggest the potential for taking account of the hierarchical context of an RT link and specialisations of the RT relationship

Source

Journal of digital information. 1(2001) no.8

0.004267752 = product of:
  0.012803256 = sum of:
    0.012803256 = product of:
      0.025606511 = sum of:
        0.025606511 = weight(_text_:of in 155) [ClassicSimilarity], result of:
          0.025606511 = score(doc=155,freq=26.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.37376386 = fieldWeight in 155, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=155)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Describes a research project, in which similarity measures have been extended to include imprecise matching over different dimensions of structured classification schemes (subject, soace, time). The semantic similarity of information units forms the basis for the automatic construction of links and is integrated into hypermedia navigation. Outlines a semantic hypermedia architecture, and a prototype museum social history application. Presents illustrative navigation scenarios which make use of a navigation via similarity tool. The temporal mesaures of semantic closeness underpin the similarity tool. The temporal measures takes account of periods as well as time points. The most general measure is based on a traversal of a semantic net, taking into account relationship type and level of specialisation. It is based on a notion of closeness rather than absolute distance, and returns a seit of semantically close terms. Discusses a methods of calculating semantic similarity between sets of index terms, based on the maximal closeness values achieved by each term

Footnote

Contribution to a special issue on methods and tools for the automatic construction of hypertext

0.0039058835 = product of:
  0.01171765 = sum of:
    0.01171765 = product of:
      0.0234353 = sum of:
        0.0234353 = weight(_text_:of in 3523) [ClassicSimilarity], result of:
          0.0234353 = score(doc=3523,freq=16.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34207192 = fieldWeight in 3523, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3523)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This work tries to propose a set of evaluation dimensions for the analysis of the knowledge organization systems (KOS), building over previous research and the available literature on the subject. It presents a compiled taxonomy of KOSs, a set of tentative characteristics proposed in the literature and the authors' spectra proposal. The full details of the typology are not covered in the scope of the article, but will be available as an ontology in the near future.

Source

Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO Conference, 23-26 February 2010 Rome, Italy. Edited by Claudio Gnoli and Fulvio Mazzocchi

0.0039058835 = product of:
  0.01171765 = sum of:
    0.01171765 = product of:
      0.0234353 = sum of:
        0.0234353 = weight(_text_:of in 139) [ClassicSimilarity], result of:
          0.0234353 = score(doc=139,freq=16.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.34207192 = fieldWeight in 139, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=139)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

This paper analyzes previous work on the classification of Knowledge Organization Systems (KOS), discusses strengths and weaknesses, and proposes a new and integrative framework. It argues that current analyses of the KOS tend to be idiosyncratic and incomplete, relying on a limited number of dimensions of analysis. The paper discusses why and how KOS should be classified on a new basis. Based on the available literature and previous work, the authors propose a wider set of dimensions for the analysis of KOS. These are represented in a taxonomy of KOS. Issues arising are discussed.

0.0037818556 = product of:
  0.011345566 = sum of:
    0.011345566 = product of:
      0.022691133 = sum of:
        0.022691133 = weight(_text_:of in 2677) [ClassicSimilarity], result of:
          0.022691133 = score(doc=2677,freq=60.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.33120972 = fieldWeight in 2677, product of:
              7.745967 = tf(freq=60.0), with freq of:
                60.0 = termFreq=60.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.02734375 = fieldNorm(doc=2677)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Source

Knowledge organization and the global information society: Proceedings of the 8th International ISKO Conference 13-16 July 2004, London, UK. Ed.: I.C. McIlwaine

0.003743066 = product of:
  0.0112291975 = sum of:
    0.0112291975 = product of:
      0.022458395 = sum of:
        0.022458395 = weight(_text_:of in 7460) [ClassicSimilarity], result of:
          0.022458395 = score(doc=7460,freq=20.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.32781258 = fieldWeight in 7460, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=7460)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Describes an integrated approach to similarity coefficients for information spaces with multiple dimensions of different types of index term. Categorises applications of similarity coefficients underlying different navigation tools in hypermedia by type of term. Describes an implementation of a unified similarity coefficient based on work in numerical taxonomy, with illustrative scenarios from an experimental navigation via similarity tool for a prototype social history museum hypermedia system. The underlying architecture is based on a semantic approach, where semantic relationships can exist between index terms. This allows imprecise matching when comparing for similarity, with distance measures yielding a degree of match. A ranked list of matching items over several weighted dimensions is returned by the similarity navigation tool. The approach has the potential of allowing different access methods to multimedia data to be combined

Source

Global complexity: information, chaos and control. Proceedings of the 59th Annual Meeting of the American Society for Information Science, ASIS'96, Baltimore, Maryland, 21-24 Oct 1996. Ed.: S. Hardin

0.003701243 = product of:
  0.011103729 = sum of:
    0.011103729 = product of:
      0.022207458 = sum of:
        0.022207458 = weight(_text_:of in 3948) [ClassicSimilarity], result of:
          0.022207458 = score(doc=3948,freq=44.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.3241498 = fieldWeight in 3948, product of:
              6.6332498 = tf(freq=44.0), with freq of:
                44.0 = termFreq=44.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=3948)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Footnote

Beitrag in einem Special Issue: Content architecture: exploiting and managing diverse resources: proceedings of the first national conference of the United Kingdom chapter of the International Society for Knowedge Organization (ISKO)

0.0036907129 = product of:
  0.011072138 = sum of:
    0.011072138 = product of:
      0.022144277 = sum of:
        0.022144277 = weight(_text_:of in 2918) [ClassicSimilarity], result of:
          0.022144277 = score(doc=2918,freq=28.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.32322758 = fieldWeight in 2918, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2918)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Source

Journal of documentation. 70(2014) no.5, S.801-828

0.00355646 = product of:
  0.0106693795 = sum of:
    0.0106693795 = product of:
      0.021338759 = sum of:
        0.021338759 = weight(_text_:of in 4171) [ClassicSimilarity], result of:
          0.021338759 = score(doc=4171,freq=26.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.31146988 = fieldWeight in 4171, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4171)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Purpose - Traditional subject indexing and classification are considered infeasible in many digital collections. This paper seeks to investigate ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Design/methodology/approach - Enhanced tagging interfaces were developed for exemplar online repositories, and trials were undertaken with author and reader groups to evaluate the effectiveness of tagging augmented with control vocabulary for subject indexing of papers in online repositories. Findings - The results showed that using a knowledge organisation system to augment tagging does appear to increase the effectiveness of non-specialist users (that is, without information science training) in subject indexing. Research limitations/implications - While limited by the size and scope of the trials undertaken, these results do point to the usefulness of a mixed approach in supporting the subject indexing of online resources. Originality/value - The value of this work is as a guide to future developments in the practical support for resource indexing in online repositories.

Footnote

Beitrag in einem Special Issue: Content architecture: exploiting and managing diverse resources: proceedings of the first national conference of the United Kingdom chapter of the International Society for Knowedge Organization (ISKO)

0.0034169364 = product of:
  0.010250809 = sum of:
    0.010250809 = product of:
      0.020501617 = sum of:
        0.020501617 = weight(_text_:of in 2215) [ClassicSimilarity], result of:
          0.020501617 = score(doc=2215,freq=24.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2992506 = fieldWeight in 2215, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2215)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Source

Journal of documentation. 62(2006) no.4, S.509-533

0.0034169364 = product of:
  0.010250809 = sum of:
    0.010250809 = product of:
      0.020501617 = sum of:
        0.020501617 = weight(_text_:of in 2895) [ClassicSimilarity], result of:
          0.020501617 = score(doc=2895,freq=24.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2992506 = fieldWeight in 2895, product of:
              4.8989797 = tf(freq=24.0), with freq of:
                24.0 = termFreq=24.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2895)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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

0.003382594 = product of:
  0.010147782 = sum of:
    0.010147782 = product of:
      0.020295564 = sum of:
        0.020295564 = weight(_text_:of in 2801) [ClassicSimilarity], result of:
          0.020295564 = score(doc=2801,freq=12.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.29624295 = fieldWeight in 2801, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2801)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Reviews claims made for virtual architectures and proposes a semantic data model for hypermedia architecture. Semantic modelling and an extended binary relational model in particular, are outlined in the context of hypermedia. The binary relational store is a simple, uniform data structure, capable of representing abstraction in the application model. Pilot implementations of museum hypermedia systems demonstrate that the architecture is capable of supporting a variety of navigation techniques and authoring tools. Outlines the SHIC (Social History and Industrial Classification) museum classification schema, and discusses its implementation in a hypermedia system based on a binary relational store. Considers experiences with the prototypes and discusses feedback from the museum profession and general public. An extended binary relational model is particularly suited to certain forms of reasoning based on generalization

0.0033478998 = product of:
  0.010043699 = sum of:
    0.010043699 = product of:
      0.020087399 = sum of:
        0.020087399 = weight(_text_:of in 2344) [ClassicSimilarity], result of:
          0.020087399 = score(doc=2344,freq=4.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2932045 = fieldWeight in 2344, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.09375 = fieldNorm(doc=2344)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Footnote

Journal of digital information. 4(2004) no.4.

0.0031316737 = product of:
  0.009395021 = sum of:
    0.009395021 = product of:
      0.018790042 = sum of:
        0.018790042 = weight(_text_:of in 202) [ClassicSimilarity], result of:
          0.018790042 = score(doc=202,freq=14.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2742677 = fieldWeight in 202, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=202)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

The authors present a model of information searching in thesaurus-enhanced search systems, intended as a reference model for system developers. The model focuses on user-system interaction and charts the specific stages of searching an indexed collection with a thesaurus. It was developed based on literature, findings from empirical studies, and analysis of existing systems. The model describes in detail the entities, processes, and decisions when interacting with a search system augmented with a thesaurus. A basic search scenario illustrates this process through the model. Graphical and textual depictions of the model are complemented by a concise matrix representation for evaluation purposes. Potential problems at different stages of the search process are discussed, together with possibilities for system developers. The aim is to set out a framework of processes, decisions, and risks involved in thesaurus-based search, within which system developers can consider potential avenues for support.

Source

Journal of the American Society for Information Science and Technology. 57(2006) no.12, S.1655-1665

0.0031192217 = product of:
  0.009357665 = sum of:
    0.009357665 = product of:
      0.01871533 = sum of:
        0.01871533 = weight(_text_:of in 3179) [ClassicSimilarity], result of:
          0.01871533 = score(doc=3179,freq=20.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.27317715 = fieldWeight in 3179, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3179)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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.

Source

Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries : JCDL 2002 ; July 14 - 18, 2002, Portland, Oregon, USA. Ed. by Gary Marchionini

0.0029591531 = product of:
  0.008877459 = sum of:
    0.008877459 = product of:
      0.017754918 = sum of:
        0.017754918 = weight(_text_:of in 2205) [ClassicSimilarity], result of:
          0.017754918 = score(doc=2205,freq=18.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.25915858 = fieldWeight in 2205, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2205)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

The concept of Linked Data has been an emerging theme within the computing and digital heritage areas in recent years. The growth and scale of Linked Data has underlined the need for greater commonality in concept referencing, to avoid local redefinition and duplication of reference resources. Achieving domain-wide agreement on common vocabularies would be an unreasonable expectation; however, datasets often already have local vocabulary resources defined, and so the prospects for large-scale interoperability can be substantially improved by creating alignment links from these local vocabularies out to common external reference resources. The ARIADNE project is undertaking large-scale integration of archaeology dataset metadata records, to create a cross-searchable research repository resource. Key to enabling this cross search will be the 'subject' metadata originating from multiple data providers, containing terms from multiple multilingual controlled vocabularies. This paper discusses various aspects of vocabulary mapping. Experience from the previous SENESCHAL project in the publication of controlled vocabularies as Linked Open Data is discussed, emphasizing the importance of unique URI identifiers for vocabulary concepts. There is a need to align legacy indexing data to the uniquely defined concepts and examples are discussed of SENESCHAL data alignment work. A case study for the ARIADNE project presents work on mapping between vocabularies, based on the Getty Art and Architecture Thesaurus as a central hub and employing an interactive vocabulary mapping tool developed for the project, which generates SKOS mapping relationships in JSON and other formats. The potential use of such vocabulary mappings to assist cross search over archaeological datasets from different countries is illustrated in a pilot experiment. The results demonstrate the enhanced opportunities for interoperability and cross searching that the approach offers.

0.00295257 = product of:
  0.00885771 = sum of:
    0.00885771 = product of:
      0.01771542 = sum of:
        0.01771542 = weight(_text_:of in 175) [ClassicSimilarity], result of:
          0.01771542 = score(doc=175,freq=28.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.25858206 = fieldWeight in 175, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=175)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

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 demonstration of a research prototype illustrates a matching function for compound descriptors, or multi-concept subject headings, that does not rely on 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 on a measure of semantic closeness between terms.The work is part of the EPSRC funded FACET project in collaboration with the UK National Museum of Science and Industry (NMSI) which includes the National Railway Museum. An export of NMSI's Collections Database is used as the dataset for the research. The J. Paul Getty Trust's Art and Architecture Thesaurus (AAT) is the main thesaurus in the project. The AAT is a widely used thesaurus (over 120,000 terms). Descriptors are organised in 7 facets representing separate conceptual classes of terms.The FACET application is a multi tiered architecture accessing a SQL Server database, with an OLE DB connection. The thesauri are stored as relational tables in the Server's database. However, a key component of the system is a parallel representation of the underlying semantic network as an in-memory structure of thesaurus concepts (corresponding to preferred terms). The structure models the hierarchical and associative interrelationships of thesaurus concepts via weighted poly-hierarchical links. Its primary purpose is real-time semantic expansion of query terms, achieved by a spreading activation semantic closeness algorithm. Queries with associated results are stored persistently using XML format data. A Visual Basic interface combines a thesaurus browser and an initial term search facility that takes into account equivalence relationships. Terms are dragged to a direct manipulation Query Builder which maintains the facet structure.

Source

Proceedings of the Second ACM/IEEE-CS Joint Conference on Digital Libraries : JCDL 2002 ; July 14 - 18, 2002, Portland, Oregon, USA. Ed. by Gary Marchionini