Abstract
This paper intend to present an approach to analyse the change of word meaning based on word embedding, which is a more general method to quantize words than before. Through analysing the similar words and clustering in different period, semantic change could be detected. We analysed the trend of semantic change through density clustering method called DBSCAN. Statics and data visualization is also included to make the result more clear. Some words like ‘gay’, ‘mouse’ are traced as case to prove this approach works. At last, we also compared the context words and similar words on semantic presentation and proved the context words worked better.
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Liao, X., Cheng, G. (2016). Analysing the Semantic Change Based on Word Embedding. In: Lin, CY., Xue, N., Zhao, D., Huang, X., Feng, Y. (eds) Natural Language Understanding and Intelligent Applications. ICCPOL NLPCC 2016 2016. Lecture Notes in Computer Science(), vol 10102. Springer, Cham. https://doi.org/10.1007/978-3-319-50496-4_18
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DOI: https://doi.org/10.1007/978-3-319-50496-4_18
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