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Erschienen in:
08.02.2018
A Study on Characteristics of MSAV Based on SAL-F Algorithm
Erschienen in: Wireless Personal Communications | Ausgabe 2/2018
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Abstract
The traditional method of lexical interpretation is to use a few words to explain some other words. Its lexical semantic information cannot be applied to natural language processing oriented towards physical contexts, on the basis of which the paper proposes a lexical semantic representation model based on graphic feature vectors and its learning algorithm Sal-F. The algorithm applies cross-situational learning to the alignment of word-graph features, establishes visual semantic model of words (Lsm-G) on the basis of the feature selection results and constructs semantic dictionary based on graphic features. According to evaluation methods such as machine translation, the algorithm achieves a word average accuracy of 70% and the highest sentence accuracy of 16%.