Multilingual Semantic Transformation through Simple Sentence Mediation

Tracking #: 2499-3713

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Peng Qin
Jingzhi Guo
Quanyi Hu

Responsible editor: 
Anna Lisa Gentile

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In multilingual semantic transformation, semantic representation faces challenges in ambiguity and consistency. It is an important research topic in document exchange and NLP. Here, in terms of document representation, current researches have not been solved a complex concept for a single cell of a table. Thus, this paper proposes a novel collaborative framework - Simple Sentence Mediation by leveraging a Semantic Input Method for sharing common atomic concepts. Besides, we design a transformation approach – a sentence-based Machine Universal Language enables any simple sentences to be represented into the bags of concepts from a sequence of atomic concepts. Our method ultimately resolves the semantic shift problems to achieve the sentence-level semantic exactness, as well as machine-readable and -understandable in the heterogeneous semantic transformation.
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