Search (22 results, page 1 of 2)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × year_i:[2010 TO 2020}
  1. Gillitzer, B.: Yewno (2017) 0.02
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    Abstract
    Yewno findet Themen und Konzepte (Suchbegriffe und ihre Abstraktionen) in englischsprachigen digitalen Texten mit Methoden des maschinellen Lernens und der künstlichen Intelligenz. Als Ergebnis Ihrer Suchanfrage werden die Konzepte, die Ihre Anfrage betreffen, in vielfältigen sachlichen Beziehungen als graphisches Netzwerk präsentiert, über das Sie einfach navigieren können. Auch versteckte thematische Beziehungen werden hier sichtbar gemacht, die vom Bekannten zu neuen Entdeckungen führen. Im Rahmen einer Pilotphase können Sie über einen interdisziplinären Ausschnitt aus aktuellen englischsprachigen Fachzeitschriften verschiedenster Fachgebiete recherchieren. Die zu den Themen gehörigen Artikel werden in Ausschnitten unmittelbar angezeigt und können in den meisten Fällen direkt als Volltext aufgerufen werden.
    "Die Bayerische Staatsbibliothek testet den semantischen "Discovery Service" Yewno als zusätzliche thematische Suchmaschine für digitale Volltexte. Der Service ist unter folgendem Link erreichbar: https://www.bsb-muenchen.de/recherche-und-service/suchen-und-finden/yewno/. Das Identifizieren von Themen, um die es in einem Text geht, basiert bei Yewno alleine auf Methoden der künstlichen Intelligenz und des maschinellen Lernens. Dabei werden sie nicht - wie bei klassischen Katalogsystemen - einem Text als Ganzem zugeordnet, sondern der jeweiligen Textstelle. Die Eingabe eines Suchwortes bzw. Themas, bei Yewno "Konzept" genannt, führt umgehend zu einer grafischen Darstellung eines semantischen Netzwerks relevanter Konzepte und ihrer inhaltlichen Zusammenhänge. So ist ein Navigieren über thematische Beziehungen bis hin zu den Fundstellen im Text möglich, die dann in sogenannten Snippets angezeigt werden. In der Test-Anwendung der Bayerischen Staatsbibliothek durchsucht Yewno aktuell 40 Millionen englischsprachige Dokumente aus Publikationen namhafter Wissenschaftsverlage wie Cambridge University Press, Oxford University Press, Wiley, Sage und Springer, sowie Dokumente, die im Open Access verfügbar sind. Nach der dreimonatigen Testphase werden zunächst die Rückmeldungen der Nutzer ausgewertet. Ob und wann dann der Schritt von der klassischen Suchmaschine zum semantischen "Discovery Service" kommt und welche Bedeutung Anwendungen wie Yewno in diesem Zusammenhang einnehmen werden, ist heute noch nicht abzusehen. Die Software Yewno wurde vom gleichnamigen Startup in Zusammenarbeit mit der Stanford University entwickelt, mit der auch die Bayerische Staatsbibliothek eng kooperiert. [Inetbib-Posting vom 22.02.2017].
    Date
    22. 2.2017 10:16:49
  2. Horch, A.; Kett, H.; Weisbecker, A.: Semantische Suchsysteme für das Internet : Architekturen und Komponenten semantischer Suchmaschinen (2013) 0.01
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    BK
    54.72 Künstliche Intelligenz
    Classification
    54.72 Künstliche Intelligenz
  3. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  4. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  5. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.01
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  6. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.01
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  7. Salaba, A.; Zeng, M.L.: Extending the "Explore" user task beyond subject authority data into the linked data sphere (2014) 0.00
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  8. Mlodzka-Stybel, A.: Towards continuous improvement of users' access to a library catalogue (2014) 0.00
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  9. Zeng, M.L.; Gracy, K.F.; Zumer, M.: Using a semantic analysis tool to generate subject access points : a study using Panofsky's theory and two research samples (2014) 0.00
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  10. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.00
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    Date
    22. 8.2014 17:07:50
  11. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.00
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  12. Vidinli, I.B.; Ozcan, R.: New query suggestion framework and algorithms : a case study for an educational search engine (2016) 0.00
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    Abstract
    Query suggestion is generally an integrated part of web search engines. In this study, we first redefine and reduce the query suggestion problem as "comparison of queries". We then propose a general modular framework for query suggestion algorithm development. We also develop new query suggestion algorithms which are used in our proposed framework, exploiting query, session and user features. As a case study, we use query logs of a real educational search engine that targets K-12 students in Turkey. We also exploit educational features (course, grade) in our query suggestion algorithms. We test our framework and algorithms over a set of queries by an experiment and demonstrate a 66-90% statistically significant increase in relevance of query suggestions compared to a baseline method.
  13. Mäkelä, E.; Hyvönen, E.; Saarela, S.; Vilfanen, K.: Application of ontology techniques to view-based semantic serach and browsing (2012) 0.00
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  14. Goslin, K.; Hofmann, M.: ¬A Wikipedia powered state-based approach to automatic search query enhancement (2018) 0.00
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  15. 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
  16. Semantic search over the Web (2012) 0.00
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    Classification
    TVK (FH K)
    GHBS
    TVK (FH K)
  17. Hu, K.; Luo, Q.; Qi, K.; Yang, S.; Mao, J.; Fu, X.; Zheng, J.; Wu, H.; Guo, Y.; Zhu, Q.: Understanding the topic evolution of scientific literatures like an evolving city : using Google Word2Vec model and spatial autocorrelation analysis (2019) 0.00
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  18. Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014) 0.00
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    Date
    20. 1.2015 18:30:22
  19. Pal, D.; Mitra, M.; Datta, K.: Improving query expansion using WordNet (2014) 0.00
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  20. Bhansali, D.; Desai, H.; Deulkar, K.: ¬A study of different ranking approaches for semantic search (2015) 0.00
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Languages

  • e 20
  • d 2

Types