{"pk":26625,"title":"Building bilingual semantic representations based on a corpus-based statisticallearning algorithm","subtitle":null,"abstract":"In the current study, we applied a corpus-based statistical learning algorithm to derive semantic representations ofwords under bilingual situations (English and Chinese). The algorithm relies on the analyses of contextual information extractedfrom a text corpus, specifically, analyses of word co-occurrences in a large-scale electronic database of text. Particularly, weexamined how the semantic structure of L2 words can be built based on and influenced by the semantic representations of L1words in a sequential L2 learning situation. We got the semantic representations under various conditions and the results wereprocessed and illustrated on self-organizing maps, an unsupervised neural network model that projects the statistical structureof the context onto a 2-D space. We further discussed a couple of factors that affected the validity of the representations.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Member Abstracts","is_remote":true,"remote_url":"https://escholarship.org/uc/item/1z98c8bs","frozenauthors":[{"first_name":"Xiaowei","middle_name":"","last_name":"Zhao","name_suffix":"","institution":"Emmanuel College","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2016-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/26625/galley/16261/download/"}]}