Search (5 results, page 1 of 1)

  • × author_ss:"Blocks, D."
  1. Tudhope, D.; Blocks, D.; Cunliffe, D.; Binding, C.: Query expansion via conceptual distance in thesaurus indexed collections (2006) 0.04
    0.038317636 = product of:
      0.19158818 = sum of:
        0.19158818 = weight(_text_:thesaurus in 2215) [ClassicSimilarity], result of:
          0.19158818 = score(doc=2215,freq=20.0), product of:
            0.23732872 = queryWeight, product of:
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.051357865 = queryNorm
            0.8072692 = fieldWeight in 2215, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2215)
      0.2 = coord(1/5)
    
    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.
    Object
    Art and architecture thesaurus
  2. Blocks, D.; Cunliffe, D.; Tudhope, D.: ¬A reference model for user-system interaction in thesaurus-based searching (2006) 0.03
    0.032513592 = product of:
      0.16256796 = sum of:
        0.16256796 = weight(_text_:thesaurus in 202) [ClassicSimilarity], result of:
          0.16256796 = score(doc=202,freq=10.0), product of:
            0.23732872 = queryWeight, product of:
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.051357865 = queryNorm
            0.68499064 = fieldWeight in 202, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.046875 = fieldNorm(doc=202)
      0.2 = coord(1/5)
    
    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.
  3. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: FACET: thesaurus retrieval with semantic term expansion (2002) 0.03
    0.027417867 = product of:
      0.13708933 = sum of:
        0.13708933 = weight(_text_:thesaurus in 175) [ClassicSimilarity], result of:
          0.13708933 = score(doc=175,freq=16.0), product of:
            0.23732872 = queryWeight, product of:
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.051357865 = queryNorm
            0.5776348 = fieldWeight in 175, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.03125 = fieldNorm(doc=175)
      0.2 = coord(1/5)
    
    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.
  4. Tudhope, D.; Binding, C.; Blocks, D.; Cuncliffe, D.: Representation and retrieval in faceted systems (2003) 0.02
    0.024234196 = product of:
      0.12117098 = sum of:
        0.12117098 = weight(_text_:thesaurus in 2703) [ClassicSimilarity], result of:
          0.12117098 = score(doc=2703,freq=8.0), product of:
            0.23732872 = queryWeight, product of:
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.051357865 = queryNorm
            0.5105618 = fieldWeight in 2703, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2703)
      0.2 = coord(1/5)
    
    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.
    Object
    Art and Architecture Thesaurus
  5. Tudhope, D.; Binding, C.; Blocks, D.; Cunliffe, D.: Compound descriptors in context : a matching function for classifications and thesauri (2002) 0.02
    0.020987432 = product of:
      0.10493716 = sum of:
        0.10493716 = weight(_text_:thesaurus in 3179) [ClassicSimilarity], result of:
          0.10493716 = score(doc=3179,freq=6.0), product of:
            0.23732872 = queryWeight, product of:
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.051357865 = queryNorm
            0.44215953 = fieldWeight in 3179, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              4.6210785 = idf(docFreq=1182, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3179)
      0.2 = coord(1/5)
    
    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.