Search (60 results, page 1 of 3)

  • × theme_ss:"Wissensrepräsentation"
  • × year_i:[2010 TO 2020}
  1. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.07
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    Date
    13.12.2017 14:17:22
  2. Assem, M. van; Rijgersberg, H.; Wigham, M.; Top, J.: Converting and annotating quantitative data tables (2010) 0.07
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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.
    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
  3. Boteram, F.: Semantische Relationen in Dokumentationssprachen : vom Thesaurus zum semantischen Netz (2010) 0.05
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    Source
    Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
  4. Kiren, T.; Shoaib, M.: ¬A novel ontology matching approach using key concepts (2016) 0.05
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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
  5. Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.04
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    Date
    26.12.2011 13:40:22
  6. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.04
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    Date
    16.11.2018 14:22:01
  7. Networked Knowledge Organisation Systems and Services - TPDL 2011 : The 10th European Networked Knowledge Organisation Systems (NKOS) Workshop (2011) 0.02
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    Content
    Programm mit Links auf die Präsentationen: Armando Stellato, Ahsan Morshed, Gudrun Johannsen, Yves Jacques, Caterina Caracciolo, Sachit Rajbhandari, Imma Subirats, Johannes Keizer: A Collaborative Framework for Managing and Publishing KOS - Christian Mader, Bernhard Haslhofer: Quality Criteria for Controlled Web Vocabularies - Ahsan Morshed, Benjamin Zapilko, Gudrun Johannsen, Philipp Mayr, Johannes Keizer: Evaluating approaches to automatically match thesauri from different domains for Linked Open Data - Johan De Smedt: SKOS extensions to cover mapping requirements - Mark Tomko: Translating biological data sets Into Linked Data - Daniel Kless: Ontologies and thesauri - similarities and differences - Antoine Isaac, Jacco van Ossenbruggen: Europeana and semantic alignment of vocabularies - Douglas Tudhope: Complementary use of ontologies and (other) KOS - Wilko van Hoek, Brigitte Mathiak, Philipp Mayr, Sascha Schüller: Comparing the accuracy of the semantic similarity provided by the Normalized Google Distance (NGD) and the Search Term Recommender (STR) - Denise Bedford: Selecting and Weighting Semantically Discovered Concepts as Social Tags - Stella Dextre Clarke, Johan De Smedt. ISO 25964-1: a new standard for development of thesauri and exchange of thesaurus data
  8. Boteram, F.; Gödert, W.; Hubrich, J.: Semantic interoperability and retrieval paradigms (2010) 0.02
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  9. Qin, J.: ¬A relation typology in knowledge organization systems : case studies in the research data management domain (2018) 0.02
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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
  10. Rousset, M.-C.; Atencia, M.; David, J.; Jouanot, F.; Ulliana, F.; Palombi, O.: Datalog revisited for reasoning in linked data (2017) 0.02
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  11. Simões, M. da Graça; Machado, L.M.; Souza, R.R.; Almeida, M.B.; Tavares Lopes, A.: Automatic indexing and ontologies : the consistency of research chronology and authoring in the context of Information Science (2018) 0.02
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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
  12. Ibekwe-SanJuan, F.: Semantic metadata annotation : tagging Medline abstracts for enhanced information access (2010) 0.02
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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.
  13. Boer, V. de; Wielemaker, J.; Gent, J. van; Hildebrand, M.; Isaac, A.; Ossenbruggen, J. van; Schreiber, G.: Supporting linked data production for cultural heritage institutes : the Amsterdam Museum case study (2012) 0.02
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  14. 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) 0.02
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  15. 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) 0.02
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  16. Becker, H.-G.; Förster, F.: Vernetztes Wissen : Ereignisse in der bibliografischen Dokumentation (2010) 0.02
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  17. Girju, R.; Beamer, B.; Rozovskaya, A.; Fister, A.; Bhat, S.: ¬A knowledge-rich approach to identifying semantic relations between nominals (2010) 0.02
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    Abstract
    This paper describes a state-of-the-art supervised, knowledge-intensive approach to the automatic identification of semantic relations between nominals in English sentences. The system employs a combination of rich and varied sets of new and previously used lexical, syntactic, and semantic features extracted from various knowledge sources such as WordNet and additional annotated corpora. The system ranked first at the third most popular SemEval 2007 Task - Classification of Semantic Relations between Nominals and achieved an F-measure of 72.4% and an accuracy of 76.3%. We also show that some semantic relations are better suited for WordNet-based models than other relations. Additionally, we make a distinction between out-of-context (regular) examples and those that require sentence context for relation identification and show that contextual data are important for the performance of a noun-noun semantic parser. Finally, learning curves show that the task difficulty varies across relations and that our learned WordNet-based representation is highly accurate so the performance results suggest the upper bound on what this representation can do.
  18. Halpin, H.; Hayes, P.J.; McCusker, J.P.; McGuinness, D.L.; Thompson, H.S.: When owl:sameAs isn't the same : an analysis of identity in linked data (2010) 0.02
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    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
  19. Sartori, F.; Grazioli, L.: Metadata guiding kowledge engineering : a practical approach (2014) 0.02
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  20. Amarger, F.; Chanet, J.-P.; Haemmerlé, O.; Hernandez, N.; Roussey, C.: SKOS sources transformations for ontology engineering : agronomical taxonomy use case (2014) 0.02
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