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181
Large-Scale Acquisition of Feature-Based Conceptual Representations from Textual Corpora
In: Proceedings of the Annual Meeting of the Cognitive Science Society ; The Annual Meeting of the Cognitive Science Society ; https://hal.archives-ouvertes.fr/hal-00507103 ; The Annual Meeting of the Cognitive Science Society, 2010, United States. 6 p (2010)
Abstract: International audience ; Methods for estimating people's conceptual knowledge have the potential to be very useful to theoretical research on conceptual semantics. Traditionally, feature-based conceptual representations have been estimated using property norm data; however, computational techniques have the potential to build such representations automatically. The automatic acquisition of feature-based conceptual representations from corpora is a challenging task, given the unconstrained nature of what can constitute a semantic feature. Existing computational methods typically do not target the full range of concept-relation-feature triples occurring in human generated norms (e.g. tiger have stripes) but rather focus on concept-feature tuples (e.g. tiger – stripes) or triples involving specific relations only. We investigate the large-scale extraction of concept-relation-feature triples and the usefulness of encyclopedic, syntactic and semantic information in guiding the extraction process. Our method extracts candidate triples (e.g. tiger have stripes, flute produce sound) from parsed corpus data and ranks them on the basis of semantic information. Our investigation shows the usefulness of external knowledge in guiding feature extraction and highlights issues of methodology and evaluation which need to be addressed in developing models for this task.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; [SCCO.COMP]Cognitive science/Computer science; [SCCO.LING]Cognitive science/Linguistics; [SCCO.NEUR]Cognitive science/Neuroscience; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; corpus-based acquisition; Distributed conceptual representations; semantic features
URL: https://hal.archives-ouvertes.fr/hal-00507103/document
https://hal.archives-ouvertes.fr/hal-00507103
https://hal.archives-ouvertes.fr/hal-00507103/file/cogsci-2010.pdf
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182
Towards unrestricted, large-scale acquisition of feature-based conceptual representations from corpus data
In: ISSN: 1570-7075 ; EISSN: 1572-8706 ; Research on Language and Computation ; https://hal.archives-ouvertes.fr/hal-00605539 ; Research on Language and Computation, Springer Verlag, 2010, 7 (2-4), pp.137-170 (2010)
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183
Investigating the cross-linguistic potential of VerbNet-style classification
In: Proceedings of CoLing ; CoLing 2010 ; https://hal.archives-ouvertes.fr/hal-00539036 ; CoLing 2010, 2010, Beijing, China, China. pp.94 (2010)
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184
Towards unrestricted, large-scale acquisition of feature-based conceptual representations from corpus data
In: Research on language and computation. - London : King's College 7 (2009) 2-4, 137-170
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OLC Linguistik
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185
LexSchem: A Large Subcategorization Lexicon for French Verbs
In: Proceedings of the Language Resources and Evaluation Conference (LREC) ; LREC 2008 ; https://hal.archives-ouvertes.fr/hal-00539025 ; LREC 2008, 2008, Marrakech, Morocco. pp.142 (2008)
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186
A large-scale classification of English verbs
In: Language resources and evaluation. - Dordrecht [u.a.] : Springer 42 (2008) 1, 21-40
BLLDB
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187
Introduction to the special issue on multiword expressions: Having a crack at a hard nut
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 19 (2005) 4, 365-377
OLC Linguistik
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188
Multiword expressions
Villavicencio, Aline (Hrsg.); Bond, Francis (Hrsg.); Korhonen, Anna (Hrsg.). - Amsterdam [u.a.] : Elsevier, 2005
BLLDB
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189
Subcategorization acquisition
Korhonen, Anna. - : University of Cambridge, Computer Laboratory, 2002
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190
Detecting verbal participation in diathesis alternations
McCarthy, Diana Frances; Korhonen, Anna. - : Association for Computational Linguistics, 1998
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191
Technologies and Tools for Lexical Acquisition
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