A Set Space Model to Capture Structural Information of a Sentence
The context of a sentence is composed of a limited number of words. This leads to the feature sparsity problem whereby the sentence's meaning is easily influenced by language phenomena such as polysemy, ambiguity and puns. To resolve these problems, the set space model (SSM) uses language chara...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8853305/ |