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Finding Semantic Similarity in Vietnamese

Authors: Dat Tien Nguyen; Son Bao Pham;

Finding Semantic Similarity in Vietnamese

Abstract

Finding semantic similarity is an important task in many natural language processing applications. Despite numerous works for popular languages, there is still limited research done for Vietnamese. In this paper, we tackle the problem of finding semantic similarity for Vietnamese using Random Indexing and Hyperspace Analogue to Language to represent the semantics of words and documents. We build a system to find synonyms in Vietnamese. Experimental results show that our system achieves accuracies of 75% for finding synonyms for verbs and 65% for synonyms for nouns.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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