Search (27 results, page 1 of 2)

  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  • × language_ss:"e"
  1. Drexel, G.: Knowledge engineering for intelligent information retrieval (2001) 0.00
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    Abstract
    This paper presents a clustered approach to designing an overall ontological model together with a general rule-based component that serves as a mapping device. By observational criteria, a multi-lingual team of experts excerpts concepts from general communication in the media. The team, then, finds equivalent expressions in English, German, French, and Spanish. On the basis of a set of ontological and lexical relations, a conceptual network is built up. Concepts are thought to be universal. Objects unique in time and space are identified by names and will be explained by the universals as their instances. Our approach relies on multi-relational descriptions of concepts. It provides a powerful tool for documentation and conceptual language learning. First and foremost, our multi-lingual, polyhierarchical ontology fills the gap of semantically-based information retrieval by generating enhanced and improved queries for internet search
  2. Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018) 0.00
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    Abstract
    A challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academic and industry. To address this challenge, semantic analysis of textual data is focused in this paper. We propose an ontology-based approach to extract semantics of textual data and define the domain of data. In other words, we semantically analyse the social data at two levels i.e. the entity level and the domain level. We have chosen Twitter as a social channel challenge for a purpose of concept proof. Domain knowledge is captured in ontologies which are then used to enrich the semantics of tweets provided with specific semantic conceptual representation of entities that appear in the tweets. Case studies are used to demonstrate this approach. We experiment and evaluate our proposed approach with a public dataset collected from Twitter and from the politics domain. The ontology-based approach leverages entity extraction and concept mappings in terms of quantity and accuracy of concept identification.
  3. Gnoli, C.; Santis, R. de; Pusterla, L.: Commerce, see also Rhetoric : cross-discipline relationships as authority data for enhanced retrieval (2015) 0.00
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    Content
    Präsentation unter: http://www.udcds.com/seminar/2015/media/slides/Gnoli_InternationalUDCSeminar2015.pdf.
  4. 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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    Abstract
    Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.
  5. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.00
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
  6. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00
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    Date
    30. 3.2001 13:32:22
  7. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  8. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  9. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.00
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  10. Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016) 0.00
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  11. Sacco, G.M.: Dynamic taxonomies and guided searches (2006) 0.00
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    Date
    22. 7.2006 17:56:22
  12. Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994) 0.00
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    Date
    30. 3.2001 13:35:22
  13. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.00
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    Source
    Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
  14. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.00
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    Date
    1. 8.1996 22:08:06
  15. 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
  16. 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
  17. Lund, K.; Burgess, C.; Atchley, R.A.: Semantic and associative priming in high-dimensional semantic space (1995) 0.00
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    Source
    Proceedings of the Seventeenth Annual Conference of the Cognitive Science Society: July 22 - 25, 1995, University of Pittsburgh / ed. by Johanna D. Moore and Jill Fain Lehmann
  18. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.00
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    Date
    16.11.2008 16:22:48
  19. 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
  20. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.00
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    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al