How to Discern Important Urgent News?
Fuente:
arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
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| _version_ | 1866910333840392192 |
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| author | Vasilyev, Oleg Bohannon, John |
| author_facet | Vasilyev, Oleg Bohannon, John |
| contents | We found that a simple property of clusters in a clustered dataset of news correlate strongly with importance and urgency of news (IUN) as assessed by LLM. We verified our finding across different news datasets, dataset sizes, clustering algorithms and embeddings. The found correlation should allow using clustering (as an alternative to LLM) for identifying the most important urgent news, or for filtering out unimportant articles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_10302 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | How to Discern Important Urgent News? Vasilyev, Oleg Bohannon, John Computation and Language We found that a simple property of clusters in a clustered dataset of news correlate strongly with importance and urgency of news (IUN) as assessed by LLM. We verified our finding across different news datasets, dataset sizes, clustering algorithms and embeddings. The found correlation should allow using clustering (as an alternative to LLM) for identifying the most important urgent news, or for filtering out unimportant articles. |
| title | How to Discern Important Urgent News? |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2402.10302 |