Abstract
Modeling of semantic space is a new and challenging research topic both in cognitive science and linguistics. Existing approaches can be classified into two different types according to how the calculation are done: either a word-by-word co-occurrence matrix or a word-by-context matrix (Riordan 2007). In this paper, we argue that the existing popular distributional semantic model (vector space model), does not adequately explain the age-ofacquisition data in Chinese. An alternatively measure of semantic proximity called PROX (Gaume et al, 2006) is applied instead. The application or PROX has interesting psycholinguistic implications. Unlike previous semantic space models, PROX can be trained with children's data as well as adult data. This allows us to test the hypothesis that children's semantic space approximates the target of acquisition: adult's semantic space. It also allows us to compare our Chinese experiment results with French results to see to attest the universality of the approximation model.
Original language | English |
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Title of host publication | PACLIC 23 - Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation |
Pages | 686-693 |
Number of pages | 8 |
Volume | 2 |
Publication status | Published - 1 Dec 2009 |
Event | 23rd Pacific Asia Conference on Language, Information and Computation, PACLIC 23 - Hong Kong, Hong Kong Duration: 3 Dec 2009 → 5 Dec 2009 |
Conference
Conference | 23rd Pacific Asia Conference on Language, Information and Computation, PACLIC 23 |
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Country/Territory | Hong Kong |
City | Hong Kong |
Period | 3/12/09 → 5/12/09 |
ASJC Scopus subject areas
- Language and Linguistics
- Computer Science (miscellaneous)