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Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-enhanced search interfaces (2002)
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- Date
- 18. 5.2002 17:29:00
- Source
- Journal of information science. 28(2002) no.2, S.111-122
-
Sacco, G.M.: Accessing multimedia infobases through dynamic taxonomies (2004)
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- Date
- 6. 1.1997 18:30:28
29. 8.2004 10:15:02
-
Gnoli, C.; Santis, R. de; Pusterla, L.: Commerce, see also Rhetoric : cross-discipline relationships as authority data for enhanced retrieval (2015)
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- Content
- Präsentation unter: http://www.udcds.com/seminar/2015/media/slides/Gnoli_InternationalUDCSeminar2015.pdf.
- Source
- Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro
-
Faaborg, A.; Lagoze, C.: Semantic browsing (2003)
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- Date
- 16.11.2008 16:26:28
- Source
- Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
-
Mlodzka-Stybel, A.: Towards continuous improvement of users' access to a library catalogue (2014)
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- Date
- 5. 9.2014 19:28:39
- 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
-
Shiri, A.A.; Revie, C.; Chowdhury, G.: Thesaurus-assisted search term selection and query expansion : a review of user-centred studies (2002)
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- Date
- 6. 1.1997 18:30:28
- Source
- Knowledge organization. 29(2002) no.1, S.1-19
-
Shiri, A.A.; Revie, C.: End-user interaction with thesauri : an evaluation of cognitive overlap in search term selection (2004)
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- Date
- 6. 1.1997 18:30:28
29. 8.2004 16:27:16
-
Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
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- Abstract
- The digital library system Daffodil is targeted at strategic support of users during the information search process. For searching, exploring and managing digital library objects it provides user-customisable information seeking patterns over a federation of heterogeneous digital libraries. In this paper evaluation results with respect to retrieval effectiveness, efficiency and user satisfaction are presented. The analysis focuses on strategic support for the scientific work-flow. Daffodil supports the whole work-flow, from data source selection over information seeking to the representation, organisation and reuse of information. By embedding high level search functionality into the scientific work-flow, the user experiences better strategic system support due to a more systematic work process. These ideas have been implemented in Daffodil followed by a qualitative evaluation. The evaluation has been conducted with 28 participants, ranging from information seeking novices to experts. The results are promising, as they support the chosen model.
- Date
- 16.11.2008 16:22:48
-
Jun, W.: ¬A knowledge network constructed by integrating classification, thesaurus and metadata in a digital library (2003)
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- Date
- 19. 1.2003 19:53:28
- Source
- Bulletin of the American Society for Information Science. 29(2003) no.2, S.24-28
-
Drexel, G.: Knowledge engineering for intelligent information retrieval (2001)
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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
-
Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018)
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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.
-
Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:17:40
-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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- Date
- 30. 3.2001 13:32:22
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Horch, A.; Kett, H.; Weisbecker, A.: Semantische Suchsysteme für das Internet : Architekturen und Komponenten semantischer Suchmaschinen (2013)
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- Abstract
- In der heutigen Zeit nimmt die Flut an Informationen exponentiell zu. In dieser »Informationsexplosion« entsteht täglich eine unüberschaubare Menge an neuen Informationen im Web: Beispielsweise 430 deutschsprachige Artikel bei Wikipedia, 2,4 Mio. Tweets bei Twitter und 12,2 Mio. Kommentare bei Facebook. Während in Deutschland vor einigen Jahren noch Google als nahezu einzige Suchmaschine beim Zugriff auf Informationen im Web genutzt wurde, nehmen heute die u.a. in Social Media veröffentlichten Meinungen und damit die Vorauswahl sowie Bewertung von Informationen einzelner Experten und Meinungsführer an Bedeutung zu. Aber wie können themenspezifische Informationen nun effizient für konkrete Fragestellungen identifiziert und bedarfsgerecht aufbereitet und visualisiert werden? Diese Studie gibt einen Überblick über semantische Standards und Formate, die Prozesse der semantischen Suche, Methoden und Techniken semantischer Suchsysteme, Komponenten zur Entwicklung semantischer Suchmaschinen sowie den Aufbau bestehender Anwendungen. Die Studie erläutert den prinzipiellen Aufbau semantischer Suchsysteme und stellt Methoden der semantischen Suche vor. Zudem werden Softwarewerkzeuge vorgestellt, mithilfe derer einzelne Funktionalitäten von semantischen Suchmaschinen realisiert werden können. Abschließend erfolgt die Betrachtung bestehender semantischer Suchmaschinen zur Veranschaulichung der Unterschiede der Systeme im Aufbau sowie in der Funktionalität.
-
Srinivasan, P.: Query expansion and MEDLINE (1996)
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- Date
- 30. 3.2001 13:52:28
-
Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000)
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- Date
- 25. 2.1997 10:29:16
-
Shiri, A.A.; Revie, C.: ¬The effects of topic complexity and familiarity on cognitive and physical moves in a thesaurus-enhanced search environment (2003)
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- Source
- Journal of information science. 29(2003) no.6, S.517-
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Green, R.: See-also relationships in the Dewey Decimal Classification (2011)
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- Date
- 6. 1.1997 18:30:28
-
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)
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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.
-
Stojanovic, N.: On the query refinement in the ontology-based searching for information (2005)
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- Date
- 5. 4.1996 15:29:15
