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Die germanistische Linguistik als Fachwissenschaft in der Lehramtsausbildung ...
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Die germanistische Linguistik als Fachwissenschaft in der Lehramtsausbildung
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In: Didaktik Deutsch : Halbjahresschrift für die Didaktik der deutschen Sprache und Literatur 24 (2019) 46, S. 19-24 (2019)
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The Social Model of Translation and Its Application to Internet Search Engines Specialized in Health: The ASEM Search Engine for Neuromuscular Diseases
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In: Meta: Translators' Journal ; 55 ; 2 ; 374-386 (2017)
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Evidence of Pragmatic Impairments in Speech and Proverb Interpretation in Schizophrenia.
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In: Symplectic Elements at Oxford ; Europe PubMed Central ; PubMed (http://www.ncbi.nlm.nih.gov/pubmed/) ; Scopus (http://www.scopus.com/home.url) ; CrossRef ; ORA review team (2015)
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Das frühneuzeitliche Japan in der Medien- und Literaturgeschichte: zur Erweiterung der gesellschaftstheoretischen Perspektive Niklas Luhmanns
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In: 01/2011 ; Workingpaper des Soziologischen Seminars ; 19 (2014)
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Towards a pragmatics of weblogs
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In: Quaderns de Filologia - Estudis Lingüístics; Vol. 12 (2007): PRAGMÁTICA, DISCURSO Y SOCIEDAD; 15-33 ; 2444-1449 ; 1135-416X (2014)
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Integración conceptual y modos de inferencia
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In: Quaderns de Filologia - Estudis Lingüístics; Vol. 14 (2009): NUEVAS PERSPECTIVAS EN LINGÜÍSTICA COGNITIVA; 193-219 ; 2444-1449 ; 1135-416X (2014)
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A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
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In: DTIC (2009)
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Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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BIT at TREC 2009 Faceted Blog Distillation Task
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In: DTIC (2009)
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The Use of a Context-Based Information Retrieval Technique
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In: DTIC (2009)
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Abstract:
Since users are faced with an ever increasing amount of data, fast and effective retrieval of required information is of vital importance. This aim of this study was to examine whether the results provided by a keyword-based technique would be improved through the use of two Latent Semantic Analysis (LSA) techniques. Participants were required to highlight query terms from within documents; one LSA technique utilized the sentence of the query term, and the other LSA technique utilized the entire document. A baseline technique, in which results were not re-ranked, also was used. Fifty participants were provided with a number of information retrieval questions which involved retrieving the documents that would be useful if writing a hypothetical report on a specified topic. Using a counterbalanced repeated-measures design, participants utilized a customized interface, which retrieved and ranked documents using the three different techniques. Although the re-ranking provided by the LSA techniques ordered the documents in a significantly more efficient manner, no significant differences were found in user performance with regard to accuracy, time taken, or documents accessed using the different techniques. However, individual differences did significantly influence results, most notably with regard to participants' scores on a comprehension test. This study highlights the importance of examining the impact of individual differences in any information retrieval system. ; Prepared in cooperation with Ohio State University, Columbus, OH. The original document contains color images.
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Keyword:
*INDEX TERMS; *INDIVIDUAL DIFFERENCES; *INFORMATION RETRIEVAL; *LATENT SEMANTIC ANALYSIS; *PERFORMANCE(HUMAN); *RANKING; *SEMANTICS; ACCURACY; COMPREHENSION; CONTEXT-BASED RETRIEVAL; Information Science; Linguistics; MAN COMPUTER INTERFACE; METHODOLOGY; PRECISION; Psychology; RANK-BIASED PRECISION; REACTION TIME; RELEVANCE ASSESSMENTS; STATISTICAL ANALYSIS
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA511612
http://www.dtic.mil/docs/citations/ADA511612
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Entity Retrieval by Hierarchical Relevance Model, Exploiting the Structure of Tables and Learning Homepage Classifiers
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In: DTIC (2009)
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PRIS at 2009 Relevance Feedback track: Experiments in Language Model for Relevance Feedback
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In: DTIC (2009)
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A Study of Faceted Blog Distillation -- PRIS at TREC 2009 Blog Track
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In: DTIC (2009)
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Microsoft Research at TREC 2009. Web and Relevance Feedback Tracks
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In: DTIC (2009)
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Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task
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In: DTIC (2009)
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UMass Robust 2005: Using Mixtures of Relevance Models for Query Expansion
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In: DTIC (2005)
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