-
Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016)
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- Date
- 1. 2.2016 18:25:22
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Robertson, A.M.; Willett, P.: Applications of n-grams in textual information systems (1998)
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- Abstract
- Provides an introduction to the use of n-grams in textual information systems, where an n-gram is a string of n, usually adjacent, characters, extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n-grams include spelling errors detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look up, text compression, and language identification
- Object
- n-grams
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bayer, O.; Höhfeld, S.; Josbächer, F.; Kimm, N.; Kradepohl, I.; Kwiatkowski, M.; Puschmann, C.; Sabbagh, M.; Werner, N.; Vollmer, U.: Evaluation of an ontology-based knowledge-management-system : a case study of Convera RetrievalWare 8.0 (2005)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
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
- Source
- Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016)
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- Abstract
- Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Goslin, K.; Hofmann, M.: ¬A Wikipedia powered state-based approach to automatic search query enhancement (2018)
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- Abstract
- This paper describes the development and testing of a novel Automatic Search Query Enhancement (ASQE) algorithm, the Wikipedia N Sub-state Algorithm (WNSSA), which utilises Wikipedia as the sole data source for prior knowledge. This algorithm is built upon the concept of iterative states and sub-states, harnessing the power of Wikipedia's data set and link information to identify and utilise reoccurring terms to aid term selection and weighting during enhancement. This algorithm is designed to prevent query drift by making callbacks to the user's original search intent by persisting the original query between internal states with additional selected enhancement terms. The developed algorithm has shown to improve both short and long queries by providing a better understanding of the query and available data. The proposed algorithm was compared against five existing ASQE algorithms that utilise Wikipedia as the sole data source, showing an average Mean Average Precision (MAP) improvement of 0.273 over the tested existing ASQE algorithms.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Stojanovic, N.: On the query refinement in the ontology-based searching for information (2005)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Veltman, K.H.: Frontiers in conceptual navigation for cultural heritage (1999)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
- Type
- m
-
Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996)
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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
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Schaefer, A.; Jordan, M.; Klas, C.-P.; Fuhr, N.: Active support for query formulation in virtual digital libraries : a case study with DAFFODIL (2005)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014)
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- Date
- 22. 8.2014 17:07:50
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
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
- Source
- Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Hemmje, M.: LyberWorld : eine 3D-basierte Benutzerschnittstelle für die computerunterstützte Informationssuche in Dokumentmengen (1993)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
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
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bettencourt, N.; Silva, N.; Barroso, J.: Semantically enhancing recommender systems (2016)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
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)
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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
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Neumann. M.: HAL: Hyperspace Analogue to Language (2012)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Hancock-Beaulieu, M.: Interactive query expansion in an OPAC : interface and retrieval issues (1995)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Mandalka, M.: Open semantic search zum unabhängigen und datenschutzfreundlichen Erschliessen von Dokumenten (2015)
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- Abstract
- Ob grösserer Leak oder Zusammenwürfeln oder (wieder) Erschliessen umfangreicherer (kollaborativer) Recherche(n) oder Archive: Immer öfter müssen im Journalismus größere Datenberge und Dokumentenberge erschlossen werden. In eine Suchmaschine integrierte Analyse-Tools helfen (halb)automatisch.
- Content
- "Open Semantic Desktop Search Zur Tagung des Netzwerk Recherche ist die Desktop Suchmaschine Open Semantic Desktop Search zum unabhängigen und datenschutzfreundlichen Erschliessen und Analysieren von Dokumentenbergen nun erstmals auch als deutschsprachige Version verfügbar. Dank mächtiger Open Source Basis kann die auf Debian GNU/Linux und Apache Solr basierende freie Software als unter Linux, Windows oder Mac lauffähige virtuelle Maschine kostenlos heruntergeladen, genutzt, weitergegeben und weiterentwickelt werden. Dokumentenberge erschliessen Ob grösserer Leak oder Zusammenwürfeln oder (wieder) Erschliessen umfangreicherer (kollaborativer) Recherche(n) oder Archive: Hin und wieder müssen größere Datenberge bzw. Dokumentenberge erschlossen werden, die so viele Dokumente enthalten, dass Mensch diese Masse an Dokumenten nicht mehr alle nacheinander durchschauen und einordnen kann. Auch bei kontinuierlicher Recherche zu Fachthemen sammeln sich mit der Zeit größere Mengen digitalisierter oder digitaler Dokumente zu grösseren Datenbergen an, die immer weiter wachsen und deren Informationen mit einer Suchmaschine für das Archiv leichter auffindbar bleiben. Moderne Tools zur Datenanalyse in Verbindung mit Enterprise Search Suchlösungen und darauf aufbauender Recherche-Tools helfen (halb)automatisch.
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Tseng, Y.-H.: Solving vocabulary problems with interactive query expansion (1998)
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- Abstract
- One of the major causes of search failures in information retrieval systems is vocabulary mismatch. Presents a solution to the vocabulary problem through 2 strategies known as term suggestion (TS) and term relevance feedback (TRF). In TS, collection specific terms are extracted from the text collection. These terms and their frequencies constitute the keyword database for suggesting terms in response to users' queries. One effect of this term suggestion is that it functions as a dynamic directory if the query is a general term that contains broad meaning. In term relevance feedback, terms extracted from the top ranked documents retrieved from the previous query are shown to users for relevance feedback. In the experiment, interactive TS provides very high precision rates while achieving similar recall rates as n-gram matching. Local TRF achieves improvement in both precision and recall rate in a full text news database and degrades slightly in recall rate in bibliographic databases due to the very limited source of information for feedback. In terms of Rijsbergen's combined measure of recall and precision, both TS and TRF achieve better performance than n-gram matching, which implies that the greater improvement in precision rate compensates the slight degradation in recall rate for TS and TRF
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
