Enhancing Accuracy of Semantic Relatedness Measurement by Word Single-Meaning Embeddings
We propose a lightweight algorithm of learning word single-meaning embeddings (WSME), by exploring WordNet synsets and Doc2vec document embeddings, to enhance the accuracy of semantic relatedness measurement. In our model, each polyseme is decomposed into a series of monosemous words with diverse Wo...
| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Makale |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
IEEE
2021-01-01
|
| Seri Bilgileri: | IEEE Access |
| Konular: | |
| Online Erişim: | https://ieeexplore.ieee.org/document/9521506/ |