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This work defines a modular late-fusion function that combines semantic similarity (cosine of embeddings) and structural similarity (bibliographic coupling) with a tunable weight alpha whose value is chosen according to the specific task.
This study highlights key curatorial and audience-acceptance challenges associated with employing AI as a “co-creator” in gallery practice, creating four visitor segments: Traditionalists, Visualists, Skeptics, and AI Enthusiasts.
A heterogeneous multivariate graph model over OpenAlex open data and a methodology based on projections (citation and co-authorship networks), interpretable structural metrics, community detection, and three screening detectors of anomalous publishing patterns are defined.
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