Overcoming data sparsity in eXtreme Multi-Label classification using word embedding-based models
Abstract The transition from the analog to the digital world generates a massive volume of data every day. Millions of user’s upload, download, and search data on and from social media, Wikipedia, YouTube, Amazon, etc. It is critical to analyze and retrieve meaningful information from millions of us...
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| Autori principali: | , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer
2026-05-01
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| Serie: | Discover Computing |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/s10791-026-10158-1 |
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