Search by Fuzzy Inference in a Children's Dictionary

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ConferenceComputer Assisted Language Learning, July 2005.
AbstractThis research aims at promoting the usage of an online children's dictionary within a context of reading comprehension and vocabulary acquisition. Inspired by document retrieval approaches developed in the areas of information retrieval (IR) research, we adapt a particular IR strategy, based on fuzzy logic, to a search in the electronic dictionary. From an unknown word, searched for by a learner, our proposed fuzzy inference process makes it possible to retrieve relevant lexical information from any entry in the dictionary. Furthermore, it organizes this information in the form of semantic maps of an adaptable size surrounding the query word. Manual construction of such semantic maps are seen as being effective for helping learners in vocabulary acquisition and reading comprehension tasks. Our research leads to a capability for building them automatically. Using concrete examples, we provide details of the calculation for the construction of semantic maps as well as for the retrieval of information. We introduce a software component which could be integrated in a computer assisted language learning (CALL) environment to promote vocabulary acquisition in L1.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48513
NPARC number8914147
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Record identifier0042a5db-b95b-46b5-ac62-fbca55f9be8b
Record created2009-04-22
Record modified2016-05-09
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