Search (5 results, page 1 of 1)

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Footnote

Teil eines Themenheftes von: Journal of digital information. 4(2004) no.4.

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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.

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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

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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.

Source

International journal on digital libraries. 2015, S.1-17 DOI: 10.1007/s00799-015-0166-y

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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