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  1. Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997) 0.01
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    Date
    1.10.2018 14:13:22
  2. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.01
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  3. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.01
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    Abstract
    Companies, governmental agencies and scientists produce a large amount of quantitative (research) data, consisting of measurements ranging from e.g. the surface temperatures of an ocean to the viscosity of a sample of mayonnaise. Such measurements are stored in tables in e.g. spreadsheet files and research reports. To integrate and reuse such data, it is necessary to have a semantic description of the data. However, the notation used is often ambiguous, making automatic interpretation and conversion to RDF or other suitable format diffiult. For example, the table header cell "f(Hz)" refers to frequency measured in Hertz, but the symbol "f" can also refer to the unit farad or the quantities force or luminous flux. Current annotation tools for this task either work on less ambiguous data or perform a more limited task. We introduce new disambiguation strategies based on an ontology, which allows to improve performance on "sloppy" datasets not yet targeted by existing systems.
    Date
    29. 7.2011 14:44:56
    Source
    The Semantic Web - ISWC 2010. 9th International Semantic Web Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I. Eds.: Peter F. Patel-Schneider et al
  4. Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004) 0.01
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    Date
    29. 7.2011 14:44:56
    Source
    Proceedings of the 3rd International Semantic Web Conference (ISWC'04). Eds. D. Plexousakis and F. van Harmelen
  5. Wen, B.; Horlings, E.; Zouwen, M. van der; Besselaar, P. van den: Mapping science through bibliometric triangulation : an experimental approach applied to water research (2017) 0.01
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    Date
    16.11.2017 13:29:12
  6. Kiren, T.; Shoaib, M.: ¬A novel ontology matching approach using key concepts (2016) 0.01
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    Abstract
    Purpose Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched. Design/methodology/approach Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson's correlation coefficient and IR measures precision, recall and F-measure. Findings Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed. Originality/value On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.
    Date
    20. 1.2015 18:30:22
  7. Sartori, F.; Grazioli, L.: Metadata guiding kowledge engineering : a practical approach (2014) 0.01
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    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  8. Amarger, F.; Chanet, J.-P.; Haemmerlé, O.; Hernandez, N.; Roussey, C.: SKOS sources transformations for ontology engineering : agronomical taxonomy use case (2014) 0.01
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    Source
    Metadata and semantics research: 8th Research Conference, MTSR 2014, Karlsruhe, Germany, November 27-29, 2014, Proceedings. Eds.: S. Closs et al
  9. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.01
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    Date
    28.11.2016 12:43:22
    Source
    http://www.personal.psu.edu/faculty/f/u/fuf1/hermeneus/Hermeneus_architecture.pdf
  10. Ibekwe-SanJuan, F.: Semantic metadata annotation : tagging Medline abstracts for enhanced information access (2010) 0.01
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    Abstract
    Purpose - The object of this study is to develop methods for automatically annotating the argumentative role of sentences in scientific abstracts. Working from Medline abstracts, sentences were classified into four major argumentative roles: objective, method, result, and conclusion. The idea is that, if the role of each sentence can be marked up, then these metadata can be used during information retrieval to seek particular types of information such as novelty, conclusions, methodologies, aims/goals of a scientific piece of work. Design/methodology/approach - Two approaches were tested: linguistic cues and positional heuristics. Linguistic cues are lexico-syntactic patterns modelled as regular expressions implemented in a linguistic parser. Positional heuristics make use of the relative position of a sentence in the abstract to deduce its argumentative class. Findings - The experiments showed that positional heuristics attained a much higher degree of accuracy on Medline abstracts with an F-score of 64 per cent, whereas the linguistic cues only attained an F-score of 12 per cent. This is mostly because sentences from different argumentative roles are not always announced by surface linguistic cues. Research limitations/implications - A limitation to the study was the inability to test other methods to perform this task such as machine learning techniques which have been reported to perform better on Medline abstracts. Also, to compare the results of the study with earlier studies using Medline abstracts, the different argumentative roles present in Medline had to be mapped on to four major argumentative roles. This may have favourably biased the performance of the sentence classification by positional heuristics. Originality/value - To the best of one's knowledge, this study presents the first instance of evaluating linguistic cues and positional heuristics on the same corpus.
    Date
    29. 8.2010 12:21:49
  11. Ejei, F.; Beheshti, M.S.H.; Rajabi, T.; Ejehi, Z.: Enriching semantic relations of basic sciences ontology (2017) 0.01
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    Date
    29. 9.2017 18:39:48
  12. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.01
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    Date
    16.11.2018 14:22:01
  13. Mainz, I.; Weller, K.; Paulsen, I.; Mainz, D.; Kohl, J.; Haeseler, A. von: Ontoverse : collaborative ontology engineering for the life sciences (2008) 0.01
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    Abstract
    Ontologien werden als eine neue Methode zur detaillierten und formalisierten Wissensrepräsentation vorgestellt, dabei liegt der Schwerpunkt auf dem Einsatz von Ontologien in den Lebenswissenschaften. Wir zeigen, dass für ausgereifte wissenschaftliche Ontologien Ansätze zur gemeinschaftlichen Erarbeitung notwendig sind. Das Ontoverse Ontologie-Wiki wird vorgestellt; es ist ein Hilfsmittel, das alle Phasen des gemeinschaftlichen Ontologieaufbaus unterstützt.
  14. Blanco, E.; Cankaya, H.C.; Moldovan, D.: Composition of semantic relations : model and applications (2010) 0.00
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    Content
    Vgl. unter: http://www.hlt.utdallas.edu/~eduardo/papers/csr_model_and_applications.pdf. Vgl. für den Proceedingsband: http://www.aclweb.org/anthology/C/C10/C10-1000.pdf.
  15. Blanco, E.; Moldovan, D.: ¬A model for composing semantic relations (2011) 0.00
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    Content
    Vgl.: http://aclweb.org/anthology-new/W/W11/W11-0106.pdf. Vgl. für den Proceedingsband: http://aclweb.org/anthology-new/W/W11/W11-0100.pdf, bzw.: http://www.meaningfactory.com/bos/pubs/BosPulman2011.pdf.
  16. Griffiths, T.L.; Steyvers, M.: ¬A probabilistic approach to semantic representation (2002) 0.00
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    Date
    29. 6.2015 14:55:01
    29. 6.2015 16:09:05
  17. Boteram, F.; Gödert, W.; Hubrich, J.: Semantic interoperability and retrieval paradigms (2010) 0.00
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  18. Davies, J.; Fensel, D.; Harmelen, F. van: Conclusions: ontology-driven knowledge management : towards the Semantic Web? (2004) 0.00
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  19. Qin, J.: ¬A relation typology in knowledge organization systems : case studies in the research data management domain (2018) 0.00
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    Source
    Challenges and opportunities for knowledge organization in the digital age: proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal / organized by: International Society for Knowledge Organization (ISKO), ISKO Spain and Portugal Chapter, University of Porto - Faculty of Arts and Humanities, Research Centre in Communication, Information and Digital Culture (CIC.digital) - Porto. Eds.: F. Ribeiro u. M.E. Cerveira
  20. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.00
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    Pages
    S.11-22

Authors

Years