Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks

Francis C.K. Wong; William Shi Yuan Wang

doi:10.1109/KIMAS.2007.369799

Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks

Francis C.K. Wong, William Shi Yuan Wang

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

8 Citations (Scopus)

Abstract

Language exhibits combinatorial productivity as complex constructions are composed of simple elements In a linear or hierarchical fashion. Complexity arises as one cannot be exposed to all possible combinations during ontogeny and yet to master a language one need to be, and very often is, able to generalise to process and comprehend constructions that are of novel combinations. Accounting for such an ability is a current challenge being tackled In connectionist research. In this study, we will first demonstrate that connectionist networks do generalise towards combinatorial productivity followed by an investigation of how the networks could achieve that.

Original language	English
Title of host publication	2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007
Pages	139-144
Number of pages	6
DOIs	https://doi.org/10.1109/KIMAS.2007.369799
Publication status	Published - 25 Sept 2007
Externally published	Yes
Event	2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007 - Waltham, MA, United States Duration: 30 Apr 2007 → 3 May 2007

Conference

Conference	2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007
Country/Territory	United States
City	Waltham, MA
Period	30/04/07 → 3/05/07

ASJC Scopus subject areas

Computer Science(all)

More information

10.1109/KIMAS.2007.369799

Cite this

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title = "Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks",

abstract = "Language exhibits combinatorial productivity as complex constructions are composed of simple elements In a linear or hierarchical fashion. Complexity arises as one cannot be exposed to all possible combinations during ontogeny and yet to master a language one need to be, and very often is, able to generalise to process and comprehend constructions that are of novel combinations. Accounting for such an ability is a current challenge being tackled In connectionist research. In this study, we will first demonstrate that connectionist networks do generalise towards combinatorial productivity followed by an investigation of how the networks could achieve that.",

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Wong, FCK & Wang, WSY 2007, Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks. in 2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007., 4227538, pp. 139-144, 2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007, Waltham, MA, United States, 30/04/07. https://doi.org/10.1109/KIMAS.2007.369799

Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks. / Wong, Francis C.K.; Wang, William Shi Yuan.
2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007. 2007. p. 139-144 4227538.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks

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