Language Model-Driven Topic Clustering and Summarization for News Articles
Topic models have been widely utilized in Topic Detection and Tracking tasks, which aim to detect, track, and describe topics from a stream of broadcast news reports. However, most existing topic models neglect semantic or syntactic information and lack readable topic descriptions. To exploit semant...
| 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/8936376/ |