Eliot is a query-time clustering and temporal visualization system for arXiv literature, evaluated via offline metrics on eight domains and a user survey showing 85% meaningful cluster labels.
Bezdek, Robert Ehrlich, and William Full
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Unsupervised clustering applied to disk-detected nanobeam electron diffraction vectors automates decomposition of polycrystalline, single-crystal, and amorphous sample components.
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Eliot: Interactively $\underline{E}$xploring Fast-Changing Scientific $\underline{Li}$terature Trends with $\underline{O}$nline Da$\underline{t}$a and Learning
Eliot is a query-time clustering and temporal visualization system for arXiv literature, evaluated via offline metrics on eight domains and a user survey showing 85% meaningful cluster labels.
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High Throughput Analysis of Nanobeam Electron Diffraction Datasets using Unsupervised Clustering
Unsupervised clustering applied to disk-detected nanobeam electron diffraction vectors automates decomposition of polycrystalline, single-crystal, and amorphous sample components.