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  1. 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) 0.10
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.07
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    Content
    One of a series of three publications influenced by the travelling exhibit Places & Spaces: Mapping Science, curated by the Cyberinfrastructure for Network Science Center at Indiana University. - Additional materials can be found at http://http://scimaps.org/atlas2. Erweitert durch: Börner, Katy. Atlas of Science: Visualizing What We Know.
    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
    LCSH
    Science / Atlases
    Science / Study and teaching / Graphic methods
    Communication in science / Data processing
    Subject
    Science / Atlases
    Science / Study and teaching / Graphic methods
    Communication in science / Data processing
  3. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.06
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
    Imprint
    Pittsburgh, PA : Carnegie Mellon University, School of Computer Science, Language Technologies Institute
  4. Hocker, J.; Schindler, C.; Rittberger, M.: Participatory design for ontologies : a case study of an open science ontology for qualitative coding schemas (2020) 0.04
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    Abstract
    Purpose The open science movement calls for transparent and retraceable research processes. While infrastructures to support these practices in qualitative research are lacking, the design needs to consider different approaches and workflows. The paper bases on the definition of ontologies as shared conceptualizations of knowledge (Borst, 1999). The authors argue that participatory design is a good way to create these shared conceptualizations by giving domain experts and future users a voice in the design process via interviews, workshops and observations. Design/methodology/approach This paper presents a novel approach for creating ontologies in the field of open science using participatory design. As a case study the creation of an ontology for qualitative coding schemas is presented. Coding schemas are an important result of qualitative research, and reuse can yield great potential for open science making qualitative research more transparent, enhance sharing of coding schemas and teaching of qualitative methods. The participatory design process consisted of three parts: a requirement analysis using interviews and an observation, a design phase accompanied by interviews and an evaluation phase based on user tests as well as interviews. Findings The research showed several positive outcomes due to participatory design: higher commitment of users, mutual learning, high quality feedback and better quality of the ontology. However, there are two obstacles in this approach: First, contradictive answers by the interviewees, which needs to be balanced; second, this approach takes more time due to interview planning and analysis. Practical implications The implication of the paper is in the long run to decentralize the design of open science infrastructures and to involve parties affected on several levels. Originality/value In ontology design, several methods exist by using user-centered design or participatory design doing workshops. In this paper, the authors outline the potentials for participatory design using mainly interviews in creating an ontology for open science. The authors focus on close contact to researchers in order to build the ontology upon the expert's knowledge.
    Date
    20. 1.2015 18:30:22
    Footnote
    Beitrag in einem Special Issue: Showcasing Doctoral Research in Information Science.
  5. Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006) 0.03
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    Series
    Lecture notes in computer science; vol.4172
    Source
    Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
  6. Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.03
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    Source
    Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22
  7. Das, S.; Roy, S.: Faceted ontological model for brain tumour study (2016) 0.03
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    Abstract
    The purpose of this work is to develop an ontology-based framework for developing an information retrieval system to cater to specific queries of users. For creating such an ontology, information was obtained from a wide range of information sources involved with brain tumour study and research. The information thus obtained was compiled and analysed to provide a standard, reliable and relevant information base to aid our proposed system. Facet-based methodology has been used for ontology formalization for quite some time. Ontology formalization involves different steps such as identification of the terminology, analysis, synthesis, standardization and ordering. A vast majority of the ontologies being developed nowadays lack flexibility. This becomes a formidable constraint when it comes to interoperability. We found that a facet-based method provides a distinct guideline for the development of a robust and flexible model concerning the domain of brain tumours. Our attempt has been to bridge library and information science and computer science, which itself involved an experimental approach. It was discovered that a faceted approach is really enduring, as it helps in the achievement of properties like navigation, exploration and faceted browsing. Computer-based brain tumour ontology supports the work of researchers towards gathering information on brain tumour research and allows users across the world to intelligently access new scientific information quickly and efficiently.
    Date
    12. 3.2016 13:21:22
  8. Bringsjord, S.; Clark, M.; Taylor, J.: Sophisticated knowledge representation and reasoning requires philosophy (2014) 0.03
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    Abstract
    What is knowledge representation and reasoning (KR&R)? Alas, a thorough account would require a book, or at least a dedicated, full-length paper, but here we shall have to make do with something simpler. Since most readers are likely to have an intuitive grasp of the essence of KR&R, our simple account should suffice. The interesting thing is that this simple account itself makes reference to some of the foundational distinctions in the field of philosophy. These distinctions also play a central role in artificial intelligence (AI) and computer science. To begin with, the first distinction in KR&R is that we identify knowledge with knowledge that such-and-such holds (possibly to a degree), rather than knowing how. If you ask an expert tennis player how he manages to serve a ball at 130 miles per hour on his first serve, and then serve a safer, topspin serve on his second should the first be out, you may well receive a confession that, if truth be told, this athlete can't really tell you. He just does it; he does something he has been doing since his youth. Yet, there is no denying that he knows how to serve. In contrast, the knowledge in KR&R must be expressible in declarative statements. For example, our tennis player knows that if his first serve lands outside the service box, it's not in play. He thus knows a proposition, conditional in form.
    Date
    9. 2.2017 19:22:14
    Source
    Philosophy, computing and information science. Eds.: R. Hagengruber u. U.V. Riss
  9. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.03
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    Content
    Submitted to the Faculty of the Computer Science and Engineering Department of the University of Engineering and Technology Lahore in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Computer Science (2009 - 009-PhD-CS-04). Vgl.: http://prr.hec.gov.pk/jspui/bitstream/123456789/8375/1/Taybah_Kiren_Computer_Science_HSR_2017_UET_Lahore_14.12.2017.pdf.
    Date
    20. 1.2015 18:30:22
    Imprint
    Lahore : University of Engineering and Technology / Department of Computer Science and Engineering
  10. Cui, H.: Competency evaluation of plant character ontologies against domain literature (2010) 0.03
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    Date
    1. 6.2010 9:55:22
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1144-1165
  11. Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.03
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    Series
    Lecture notes in computer science: Lecture notes in artificial intelligence ; 4604
    Source
    Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
  12. Baião Salgado Silva, G.; Lima, G.Â. Borém de Oliveira: Using topic maps in establishing compatibility of semantically structured hypertext contents (2012) 0.03
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    Abstract
    Considering the characteristics of hypertext systems and problems such as cognitive overload and the disorientation of users, this project studies subject hypertext documents that have undergone conceptual structuring using facets for content representation and improvement of information retrieval during navigation. The main objective was to assess the possibility of the application of topic map technology for automating the compatibilization process of these structures. For this purpose, two dissertations from the UFMG Information Science Post-Graduation Program were adopted as samples. Both dissertations had been duly analyzed and structured on the MHTX (Hypertextual Map) prototype database. The faceted structures of both dissertations, which had been represented in conceptual maps, were then converted into topic maps. It was then possible to use the merge property of the topic maps to promote the semantic interrelationship between the maps and, consequently, between the hypertextual information resources proper. The merge results were then analyzed in the light of theories dealing with the compatibilization of languages developed within the realm of information technology and librarianship from the 1960s on. The main goals accomplished were: (a) the detailed conceptualization of the merge process of the topic maps, considering the possible compatibilization levels and the applicability of this technology in the integration of faceted structures; and (b) the production of a detailed sequence of steps that may be used in the implementation of topic maps based on faceted structures.
    Date
    22. 2.2013 11:39:23
  13. Conde, A.; Larrañaga, M.; Arruarte, A.; Elorriaga, J.A.; Roth, D.: litewi: a combined term extraction and entity linking method for eliciting educational ontologies from textbooks (2016) 0.03
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    Date
    22. 1.2016 12:38:14
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.2, S.380-399
  14. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.03
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  15. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.02
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    Pages
    S.11-22
  16. Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017) 0.02
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    Date
    13.12.2017 14:17:22
  17. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.02
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    Date
    26.12.2011 13:22:07
  18. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.02
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    Date
    30. 5.2010 16:22:35
  19. Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018) 0.02
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    Source
    Spektrum der Wissenschaft. 2018, H.1, S.22-27
  20. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01
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    Date
    31. 7.2010 16:58:22

Authors

Years

Languages

  • e 170
  • d 16
  • pt 2
  • More… Less…

Types

  • a 149
  • el 33
  • m 19
  • x 12
  • s 9
  • n 2
  • p 2
  • r 1
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Subjects