Search (6 results, page 1 of 1)

5.8054324E-4 = product of:
  0.009869236 = sum of:
    0.009869236 = weight(_text_:in in 3347) [ClassicSimilarity], result of:
      0.009869236 = score(doc=3347,freq=20.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.2376267 = fieldWeight in 3347, product of:
          4.472136 = tf(freq=20.0), with freq of:
            20.0 = termFreq=20.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3347)
  0.05882353 = coord(1/17)

Abstract

The cultural heritage sector has embraced social tagging as a way to increase both access to online content and to engage users with their digital collections. In this article, we build on two current lines of research. (a) We use Waisda?, an existing labeling game, to add time-based annotations to content. (b) In this context, we investigate the role of experts in human-based computation (nichesourcing). We report on a small-scale experiment in which we applied Waisda? to content from film archives. We study the differences in the type of time-based tags between experts and novices for film clips in a crowdsourcing setting. The findings show high similarity in the number and type of tags (mostly factual). In the less frequent tags, however, experts used more domain-specific terms. We conclude that competitive games are not suited to elicit real expert-level descriptions. We also confirm that providing guidelines, based on conceptual frameworks that are more suited to moving images in a time-based fashion, could result in increasing the quality of the tags, thus allowing for creating more tag-based innovative services for online audiovisual heritage.

4.926073E-4 = product of:
  0.008374324 = sum of:
    0.008374324 = weight(_text_:in in 4648) [ClassicSimilarity], result of:
      0.008374324 = score(doc=4648,freq=10.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.20163295 = fieldWeight in 4648, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4648)
  0.05882353 = coord(1/17)

Abstract

The main objective of the MultimediaN E-Culture project is to demonstrate how novel semantic-web and presentation technologies can be deployed to provide better indexing and search support within large virtual collections of culturalheritage resources. The architecture is fully based on open web standards in particular XML, SVG, RDF/OWL and SPARQL. One basic hypothesis underlying this work is that the use of explicit background knowledge in the form of ontologies/vocabularies/thesauri is in particular useful in information retrieval in knowledge-rich domains. This paper gives some details about the internals of the demonstrator.

4.8571738E-4 = product of:
  0.008257195 = sum of:
    0.008257195 = weight(_text_:in in 265) [ClassicSimilarity], result of:
      0.008257195 = score(doc=265,freq=14.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.19881277 = fieldWeight in 265, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0390625 = fieldNorm(doc=265)
  0.05882353 = coord(1/17)

Abstract

Within the cultural heritage field, proprietary metadata and vocabularies are being transformed into public Linked Data. These efforts have mostly been at the level of large-scale aggregators such as Europeana where the original data is abstracted to a common format and schema. Although this approach ensures a level of consistency and interoperability, the richness of the original data is lost in the process. In this paper, we present a transparent and interactive methodology for ingesting, converting and linking cultural heritage metadata into Linked Data. The methodology is designed to maintain the richness and detail of the original metadata. We introduce the XMLRDF conversion tool and describe how it is integrated in the ClioPatria semantic web toolkit. The methodology and the tools have been validated by converting the Amsterdam Museum metadata to a Linked Data version. In this way, the Amsterdam Museum became the first 'small' cultural heritage institution with a node in the Linked Data cloud.

Series

Lecture notes in computer science; 7295

Source

9th Extended Semantic Web Conference (ESWC), 2012-05-27/2012-05-31 in Hersonissos, Crete, Greece. Eds.: Elena Simperl et al

4.4060132E-4 = product of:
  0.0074902223 = sum of:
    0.0074902223 = weight(_text_:in in 4646) [ClassicSimilarity], result of:
      0.0074902223 = score(doc=4646,freq=8.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.18034597 = fieldWeight in 4646, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=4646)
  0.05882353 = coord(1/17)

Abstract

In this article we describe a SemanticWeb application for semantic annotation and search in large virtual collections of cultural-heritage objects, indexed with multiple vocabularies. During the annotation phase we harvest, enrich and align collection metadata and vocabularies. The semantic-search facilities support keyword-based queries of the graph (currently 20M triples), resulting in semantically grouped result clusters, all representing potential semantic matches of the original query. We show two sample search scenario's. The annotation and search software is open source and is already being used by third parties. All software is based on establishedWeb standards, in particular HTML/XML, CSS, RDF/OWL, SPARQL and JavaScript.

3.1155223E-4 = product of:
  0.0052963877 = sum of:
    0.0052963877 = weight(_text_:in in 3107) [ClassicSimilarity], result of:
      0.0052963877 = score(doc=3107,freq=4.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.12752387 = fieldWeight in 3107, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.046875 = fieldNorm(doc=3107)
  0.05882353 = coord(1/17)

Abstract

The Europeana Sounds project aims to increase the amount of cultural audio content in Europeana. It also strongly focuses on enriching the metadata records that are aggregated by Europeana. To provide metadata to Europeana, Data Providers are asked to convert their records from the format and model they use internally to a specific profile of the Europeana Data Model (EDM) for sound resources. These metadata include subjects, which typically use a vocabulary internal to each partner.

2.570174E-4 = product of:
  0.004369296 = sum of:
    0.004369296 = weight(_text_:in in 59) [ClassicSimilarity], result of:
      0.004369296 = score(doc=59,freq=2.0), product of:
        0.04153252 = queryWeight, product of:
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.030532904 = queryNorm
        0.10520181 = fieldWeight in 59, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.3602545 = idf(docFreq=30841, maxDocs=44218)
          0.0546875 = fieldNorm(doc=59)
  0.05882353 = coord(1/17)

Abstract

Many Semantic Web applications provide access to their resources through text-based search queries, using explicit semantics to improve the search results. This paper provides an analysis of the current state of the art in semantic search, based on 35 existing systems. We identify different types of semantic search features that are used during query construction, the core search process, the presentation of the search results and user feedback on query and results. For each of these, we consider the functionality that the system provides and how this is made available through the user interface.