Measuring Similarity: Computationally Reproducing the Scholar's Interests
원문 초록
Computerized document classification already orders the news articles that Apple's "News" app or Google's "personalized search" feature groups together to match a reader's interests. The invisible and therefore illegible decisions that go into these tailored searches have been the subject of a critique by scholars who emphasize that our intelligence about documents is only as good as our ability to understand the criteria of search. This article will attempt to unpack the procedures used in computational classification of texts, translating them into term legible to humanists, and examining opportunities to render the computational text classification process subject to expert critique and improvement.
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Small Language Models in the Real World: Insights from Industrial Text Classification
Classifying the Ideological Orientation of User-Submitted Texts in Social Media
토론
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