Learning distributed sentence representations for story segmentation
Traditional sentence representations such as bag-of-words (BOW) and term frequency-inverse document frequency (tf-idf) face the problem of data sparsity and may not generalize well. Neural network based representations such as word/sentence vectors are usually trained in an unsupervised way and lack...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/141962 |
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| Institution: | Nanyang Technological University |
| Language: | English |