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Measuring Similarity: Computationally Reproducing the Scholar's Interests

2018/12/14 by Ashley Lee, Jo Guldi, Lee, Ashley +3
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cs.CL

paper · pdf · doi:10.48550/arxiv.1812.05984

to be submitted

arxiv created 2018/12/14 · arxiv updated 2018/12/17

Abstract

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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