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Brief

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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. BioArtlas: Computational Clustering of Multi-Dimensional Complexity in Bioart

    Joonhyung Bae has developed BioArtlas, a computational tool designed to organize and analyze the field of bioart. This atlas represents bioartworks across multiple curated dimensions, enabling comparison based on conceptual similarity rather than traditional categories like medium or chronology. BioArtlas utilizes agglomerative clustering, achieving a silhouette score of 0.664, which significantly outperforms the common k-means baseline of 0.483 in separating the field into distinct clusters. The project aims to transform the complex landscape of bioart into a navigable space, providing both an interactive interface and an open dataset. AI