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Logical validation, answer merging and witness selection: A study in multi-stream question answering
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In: http://pi7.fernuni-hagen.de/papers/gloeckner_hartrumpf_etal07.pdf (2007)
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University of Hagen at QA@CLEF 2007: Coreference Resolution for Questions and Answer Merging
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In: http://www.clef-campaign.org/2007/working_notes/hartrumpfCLEF2007.pdf (2007)
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The Role of Intensional and Extensional Interpretation in Semantic Representations -- The Intensional and Preextensional Layers in MultiNet
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In: http://pi7.fernuni-hagen.de/gloeckner/nlpcs07.pdf (2007)
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Logical Validation, Answer Merging and Witness Selection A Study in Multi-Stream Question Answering
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In: http://riao.free.fr/papers/65.pdf (2007)
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Automatic knowledge acquisition by semantic analysis and assimilation of textual information
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In: http://pi7.fernuni-hagen.de/gloeckner/konvens06-assim.pdf (2006)
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Answer validation through robust logical inference
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In: http://pi7.fernuni-hagen.de/gloeckner/glocknerCLEF2006.pdf (2006)
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Fuzzy Quantifiers: A Natural Language Technique for Data Fusion
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In: http://sunknoll1.informatik.tu-muenchen.de/~knoll/publikationen/fusion2001.pdf (2001)
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Abstract:
Fuzzy quantifiers like ‘almost all’ and ‘about half’ abound in natural language. They are used for describing uncertain facts, quantitative relations and processes. An implementation of these quantifiers can provide expressive and easy-to-use operators for aggregation and data fusion, but also for steering the fusion process on a higher level through a safe transfer of expert-knowledge expressed in natural language. However, existing approaches to fuzzy quantification are linguistically inconsistent in many common and relevant situations. To overcome their deficiencies, we developed a new framework for fuzzy quantification, DFS. We first present the axioms of the theory, intended to formalize the notion of ‘linguistic adequacy’. We then argue that the models of the theory are plausible from a linguistic perspective. We present three computational models and discuss some of their properties. Finally we provide an application example based on image data.
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Keyword:
Fuzzy quantifiers; linguistic data fusion
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.111.991 http://sunknoll1.informatik.tu-muenchen.de/~knoll/publikationen/fusion2001.pdf
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Fuzzy Quantifiers for Data Summarization and their Role in Granular Computing
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In: http://www6.in.tum.de/~knoll/publikationen/ifsa2001.pdf (2001)
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A formal theory of fuzzy natural language quantification and its role in granular computing
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In: http://sunknoll1.informatik.tu-muenchen.de/~knoll/publikationen/pchapter.pdf (2001)
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An Axiomatic Theory of Fuzzy Quantifiers in Natural Languages
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In: http://kassandra.techfak.uni-bielefeld.de/ingo/tr2k3.pdf (2000)
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A Framework for Evaluating Approaches to Fuzzy Quantification
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In: http://www.techfak.uni-bielefeld.de/techfak/ags/ti/forschung/publikationen/tr99-03.ps.gz (1999)
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A Framework for Evaluating Fusion Operators Based on the Theory of Generalized Quantifiers
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In: http://www.techfak.uni-bielefeld.de/techfak/ags/ti/personen/ingo/mfi99.ps.gz (1999)
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University of Hagen at CLEF 2008: Answer Validation Exercise
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In: http://www.clef-campaign.org/2008/working_notes/glockner-AVE-paperCLEF2008.pdf
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University of Hagen at CLEF 2007: Answer Validation Exercise
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In: http://www.clef-campaign.org/2007/working_notes/glocknerclef2007.pdf
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The LogAnswer Project at ResPubliQA 2010
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In: http://clef2010.org/resources/proceedings/clef2010labs_submission_30.pdf
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Optimal Selection of Proportional Bounding Quantifiers in Linguistic Data Summarization
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In: http://pi7.fernuni-hagen.de/gloeckner/smps06-gloeckner.pdf
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Towards Logic-Based Question Answering under Time Constraints
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In: http://www.iaeng.org/publication/IMECS2008/IMECS2008_pp13-18.pdf
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Efficient Question Answering with Question Decomposition and Multiple Answer Streams
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In: http://www.clef-campaign.org/2008/working_notes/hartrumpf-paperCLEF2008.pdf
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Combining Theorem Proving with Natural Language Processing
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In: http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-373/paper-06.pdf
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