-
Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003)
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- Date
- 22. 3.2003 19:35:46
- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.4, S.321-334
-
Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006)
0.03
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- Date
- 22. 7.2006 16:32:43
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.4, S.462-478
-
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
-
Sacco, G.M.: Dynamic taxonomies and guided searches (2006)
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- Date
- 22. 7.2006 17:56:22
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Faaborg, A.; Lagoze, C.: Semantic browsing (2003)
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- Source
- Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Date
- 11. 2.2011 18:22:58
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Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005)
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- Date
- 11. 2.2011 18:22:25
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Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
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- Date
- 16.11.2008 16:22:48
-
Schek, M.: Automatische Klassifizierung und Visualisierung im Archiv der Süddeutschen Zeitung (2005)
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- Abstract
- DIZ definiert das Wissensnetz als Alleinstellungsmerkmal und wendet beträchtliche personelle Ressourcen für die Aktualisierung und Oualitätssicherung der Dossiers auf. Nach der Umstellung auf den komplett digitalisierten Workflow im April 2001 identifizierte DIZ vier Ansatzpunkte, wie die Aufwände auf der Inputseite (Lektorat) zu optimieren sind und gleichzeitig auf der Outputseite (Recherche) das Wissensnetz besser zu vermarkten ist: 1. (Teil-)Automatische Klassifizierung von Pressetexten (Vorschlagwesen) 2. Visualisierung des Wissensnetzes (Topic Mapping) 3. (Voll-)Automatische Klassifizierung und Optimierung des Wissensnetzes 4. Neue Retrievalmöglichkeiten (Clustering, Konzeptsuche) Die Projekte 1 und 2 "Automatische Klassifizierung und Visualisierung" starteten zuerst und wurden beschleunigt durch zwei Entwicklungen: - Der Bayerische Rundfunk (BR), ursprünglich Mitbegründer und 50%-Gesellschafter der DIZ München GmbH, entschloss sich aus strategischen Gründen, zum Ende 2003 aus der Kooperation auszusteigen. - Die Medienkrise, hervorgerufen durch den massiven Rückgang der Anzeigenerlöse, erforderte auch im Süddeutschen Verlag massive Einsparungen und die Suche nach neuen Erlösquellen. Beides führte dazu, dass die Kapazitäten im Bereich Pressedokumentation von ursprünglich rund 20 (nur SZ, ohne BR-Anteil) auf rund 13 zum 1. Januar 2004 sanken und gleichzeitig die Aufwände für die Pflege des Wissensnetzes unter verstärkten Rechtfertigungsdruck gerieten. Für die Projekte 1 und 2 ergaben sich daraus drei quantitative und qualitative Ziele: - Produktivitätssteigerung im Lektorat - Konsistenzverbesserung im Lektorat - Bessere Vermarktung und intensivere Nutzung der Dossiers in der Recherche Alle drei genannten Ziele konnten erreicht werden, wobei insbesondere die Produktivität im Lektorat gestiegen ist. Die Projekte 1 und 2 "Automatische Klassifizierung und Visualisierung" sind seit Anfang 2004 erfolgreich abgeschlossen. Die Folgeprojekte 3 und 4 laufen seit Mitte 2004 und sollen bis Mitte 2005 abgeschlossen sein. Im folgenden wird in Abschnitt 2 die Produktauswahl und Arbeitsweise der Automatischen Klassifizierung beschrieben. Abschnitt 3 schildert den Einsatz der Wissensnetz-Visualisierung in Lektorat und Recherche. Abschnitt 4 fasst die Ergebnisse der Projekte 1 und 2 zusammen und gibt einen Ausblick auf die Ziele der Projekte 3 und 4.
-
Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007)
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- Source
- Information processing and management. 43(2007) no.4, S.866-886
-
Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006)
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- Source
- Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
-
Rahmstorf, G.: Integriertes Management inhaltlicher Datenarten (2001)
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- Series
- Tagungen der Deutschen Gesellschaft für Informationswissenschaft und Informationspraxis; 4
-
Nie, J.-Y.: Query expansion and query translation as logical inference (2003)
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- Source
- Journal of the American Society for Information Science and technology. 54(2003) no.4, S.335-346
-
Tudhope, D.; Blocks, D.; Cunliffe, D.; Binding, C.: Query expansion via conceptual distance in thesaurus indexed collections (2006)
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- Source
- Journal of documentation. 62(2006) no.4, S.509-533
-
Hauer, M: Silicon Valley Vorarlberg : Maschinelle Indexierung und semantisches Retrieval verbessert den Katalog der Vorarlberger Landesbibliothek (2004)
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- Source
- Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 57(2004) H.3/4, S.33-38
-
Lehtokangas, R.; Järvelin, K.: Consistency of textual expression in newspaper articles : an argument for semantically based query expansion (2001)
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- Source
- Journal of documentation. 57(2001) no.4, S.535-548
-
Li, D.; Kwong, C.-P.; Lee, D.L.: Unified linear subspace approach to semantic analysis (2009)
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- Date
- 4. 2.2010 20:59:42
-
Efthimiadis, E.N.: Interactive query expansion : a user-based evaluation in a relevance feedback environment (2000)
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- Abstract
- A user-centered investigation of interactive query expansion within the context of a relevance feedback system is presented in this article. Data were collected from 25 searches using the INSPEC database. The data collection mechanisms included questionnaires, transaction logs, and relevance evaluations. The results discuss issues that relate to query expansion, retrieval effectiveness, the correspondence of the on-line-to-off-line relevance judgments, and the selection of terms for query expansion by users (interactive query expansion). The main conclusions drawn from the results of the study are that: (1) one-third of the terms presented to users in a list of candidate terms for query expansion was identified by the users as potentially useful for query expansion. (2) These terms were mainly judged as either variant expressions (synonyms) or alternative (related) terms to the initial query terms. However, a substantial portion of the selected terms were identified as representing new ideas. (3) The relationships identified between the five best terms selected by the users for query expansion and the initial query terms were that: (a) 34% of the query expansion terms have no relationship or other type of correspondence with a query term; (b) 66% of the remaining query expansion terms have a relationship to the query terms. These relationships were: narrower term (46%), broader term (3%), related term (17%). (4) The results provide evidence for the effectiveness of interactive query expansion. The initial search produced on average three highly relevant documents; the query expansion search produced on average nine further highly relevant documents. The conclusions highlight the need for more research on: interactive query expansion, the comparative evaluation of automatic vs. interactive query expansion, the study of weighted Webbased or Web-accessible retrieval systems in operational environments, and for user studies in searching ranked retrieval systems in general
