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1
Logical validation, answer merging and witness selection: A study in multi-stream question answering
In: http://pi7.fernuni-hagen.de/papers/gloeckner_hartrumpf_etal07.pdf (2007)
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2
University of Hagen at QA@CLEF 2007: Coreference Resolution for Questions and Answer Merging
In: http://www.clef-campaign.org/2007/working_notes/hartrumpfCLEF2007.pdf (2007)
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3
The Role of Intensional and Extensional Interpretation in Semantic Representations -- The Intensional and Preextensional Layers in MultiNet
In: http://pi7.fernuni-hagen.de/gloeckner/nlpcs07.pdf (2007)
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4
Logical Validation, Answer Merging and Witness Selection A Study in Multi-Stream Question Answering
In: http://riao.free.fr/papers/65.pdf (2007)
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5
Automatic knowledge acquisition by semantic analysis and assimilation of textual information
In: http://pi7.fernuni-hagen.de/gloeckner/konvens06-assim.pdf (2006)
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6
Answer validation through robust logical inference
In: http://pi7.fernuni-hagen.de/gloeckner/glocknerCLEF2006.pdf (2006)
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7
Fuzzy Quantifiers: A Natural Language Technique for Data Fusion
In: http://sunknoll1.informatik.tu-muenchen.de/~knoll/publikationen/fusion2001.pdf (2001)
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.
Keyword: Fuzzy quantifiers; linguistic data fusion
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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8
Fuzzy Quantifiers for Data Summarization and their Role in Granular Computing
In: http://www6.in.tum.de/~knoll/publikationen/ifsa2001.pdf (2001)
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9
A formal theory of fuzzy natural language quantification and its role in granular computing
In: http://sunknoll1.informatik.tu-muenchen.de/~knoll/publikationen/pchapter.pdf (2001)
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10
An Axiomatic Theory of Fuzzy Quantifiers in Natural Languages
In: http://kassandra.techfak.uni-bielefeld.de/ingo/tr2k3.pdf (2000)
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11
A Framework for Evaluating Approaches to Fuzzy Quantification
In: http://www.techfak.uni-bielefeld.de/techfak/ags/ti/forschung/publikationen/tr99-03.ps.gz (1999)
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12
A Framework for Evaluating Fusion Operators Based on the Theory of Generalized Quantifiers
In: http://www.techfak.uni-bielefeld.de/techfak/ags/ti/personen/ingo/mfi99.ps.gz (1999)
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13
University of Hagen at CLEF 2008: Answer Validation Exercise
In: http://www.clef-campaign.org/2008/working_notes/glockner-AVE-paperCLEF2008.pdf
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14
University of Hagen at CLEF 2007: Answer Validation Exercise
In: http://www.clef-campaign.org/2007/working_notes/glocknerclef2007.pdf
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15
The LogAnswer Project at ResPubliQA 2010
In: http://clef2010.org/resources/proceedings/clef2010labs_submission_30.pdf
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16
Optimal Selection of Proportional Bounding Quantifiers in Linguistic Data Summarization
In: http://pi7.fernuni-hagen.de/gloeckner/smps06-gloeckner.pdf
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17
Towards Logic-Based Question Answering under Time Constraints
In: http://www.iaeng.org/publication/IMECS2008/IMECS2008_pp13-18.pdf
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18
Efficient Question Answering with Question Decomposition and Multiple Answer Streams
In: http://www.clef-campaign.org/2008/working_notes/hartrumpf-paperCLEF2008.pdf
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19
Combining Theorem Proving with Natural Language Processing
In: http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-373/paper-06.pdf
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