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Exploiting Class Labels to Boost Performance on Embedding-based Text Classification
[article]
2020
arXiv
pre-print
Text classification is one of the most frequent tasks for processing textual data, facilitating among others research from large-scale datasets. Embeddings of different kinds have recently become the de facto standard as features used for text classification. These embeddings have the capacity to capture meanings of words inferred from occurrences in large external collections. While they are built out of external collections, they are unaware of the distributional characteristics of words in
arXiv:2006.02104v2
fatcat:tjl2ki6vvnat5miozcmyrhowcq