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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)
Abstract: Automatic knowledge acquisition is one of the bottlenecks in artificial intelligence and large-scale applications of natural language processing (NLP). There are many efforts to create large knowledge bases (KBs) or to automatically derive knowledge from large text corpora. On the one hand, we meet KBs like CYC, where a tremendous amount of work has been invested by knowledge enterers who have manually formalized large stocks of knowledge. The other extreme are projects using flat (mostly statistically based) methods for extracting knowledge from texts. These techniques seldom produce results with a clear semantic interpretation and sufficient quality for NLP applications, however. MAC-QUIK is a project to automatically acquire knowledge from natural language sources (like text corpora or lexicons) by means of a deep syntacticosemantic analysis and subsequent assimilation of the generated representations into a coherent KB. The paper emphasizes the role of a homogeneous formalism for interfacing between NLP and inferential question answering, and it demonstrates its use for a deductive treatment of coreference resolution.
URL: http://pi7.fernuni-hagen.de/gloeckner/konvens06-assim.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.3726
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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)
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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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