Search (8 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Semantic Web"
  • × type_ss:"a"
  • × year_i:[2010 TO 2020}
  1. Papadakis, I. et al.: Highlighting timely information in libraries through social and semantic Web technologies (2016) 0.06
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  2. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.02
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    Abstract
    Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.
    Date
    20. 1.2015 18:30:22
  3. LeBoeuf, P.: ¬A strange model named FRBRoo (2012) 0.01
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    Abstract
    Libraries and museums developed rules for the description of their collections prior to formalizing the underlying conceptualization reflected in such rules. That formalizing process took place in the 1990s and resulted in two independent conceptual models: FRBR for bibliographic information (published in 1998), and CIDOC CRM for museum information (developed from 1996 on, and issued as ISO standard 21127 in 2006). An international working group was formed in 2003 with the purpose of harmonizing these two models. The resulting model, FRBROO, was published in 2009. It is an extension to CIDOC CRM, using the formalism in which the former is written. It adds to FRBR the dynamic aspects of CIDOC CRM, and a number of refinements (e.g. in the definitions of Work and Manifestation). Some modifications were made in CIDOC CRM as well. FRBROO was developed with Semantic Web technologies in mind, and lends itself well to the Linked Data environment; but will it be used in that context?
  4. Neumaier, S.: Data integration for open data on the Web (2017) 0.01
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    Abstract
    In this lecture we will discuss and introduce challenges of integrating openly available Web data and how to solve them. Firstly, while we will address this topic from the viewpoint of Semantic Web research, not all data is readily available as RDF or Linked Data, so we will give an introduction to different data formats prevalent on the Web, namely, standard formats for publishing and exchanging tabular, tree-shaped, and graph data. Secondly, not all Open Data is really completely open, so we will discuss and address issues around licences, terms of usage associated with Open Data, as well as documentation of data provenance. Thirdly, we will discuss issues connected with (meta-)data quality issues associated with Open Data on the Web and how Semantic Web techniques and vocabularies can be used to describe and remedy them. Fourth, we will address issues about searchability and integration of Open Data and discuss in how far semantic search can help to overcome these. We close with briefly summarizing further issues not covered explicitly herein, such as multi-linguality, temporal aspects (archiving, evolution, temporal querying), as well as how/whether OWL and RDFS reasoning on top of integrated open data could be help.
  5. Hooland, S. van; Verborgh, R.; Wilde, M. De; Hercher, J.; Mannens, E.; Wa, R.Van de: Evaluating the success of vocabulary reconciliation for cultural heritage collections (2013) 0.00
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    Date
    22. 3.2013 19:29:20
  6. Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.00
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    Source
    Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22
  7. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.00
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    Date
    16.11.2018 14:22:01
  8. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.00
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    Date
    20. 1.2015 18:30:22