10 citations · 10 across the 4 of their papers we have counts for
4 papers
Radical-level Ideograph Encoder for RNN-based Sentiment Analysis of Chinese and Japanese
Yuanzhi Ke, Masafumi Hagiwara
The character vocabulary can be very large in non-alphabetic languages such as Chinese and Japanese, which makes neural network models huge to process such languages. We explored a…
Improve Lexicon-based Word Embeddings By Word Sense Disambiguation
Yuanzhi Ke, Masafumi Hagiwara
There have been some works that learn a lexicon together with the corpus to improve the word embeddings. However, they either model the lexicon separately but update the neural net…
Alleviating Overfitting for Polysemous Words for Word Representation Estimation Using Lexicons
Yuanzhi Ke, Masafumi Hagiwara
Though there are some works on improving distributed word representations using lexicons, the improper overfitting of the words that have multiple meanings is a remaining issue det…
Fuzzy paraphrases in learning word representations with a lexicon
Yuanzhi Ke, Masafumi Hagiwara
A synonym of a polysemous word is usually only the paraphrase of one sense among many. When lexicons are used to improve vector-space word representations, such paraphrases are unr…