Detecting Media Clones in Cultural Repositories Using a Positive Unlabeled Learning Approach
Year: 2025
Type: conference-paper
Abstract: Digital repositories amplify cultural-heritage research but also compound curatorial burdens such as cross-record duplicates and near-duplicates of the same artefact. We formulate curator-in-the-loop clone detection in AtticPOT as a Positive–Unlabeled (PU) learning problem. From a single anchor per artefact, a lightweight per-query Clone Encoder is trained on augmented views and uses an interpretable latent ℓ2-norm threshold to screen the unlabeled repository. The method avoids explicit negatives, exposes a transparent operating point, and integrates naturally with de-duplication, record linkage, and “find-similar” workflows.
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7137996122
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