Avory C. Bryant

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'The identification of potential breakthroughs before they happen' is a vague data analysis problem and 'the scientific literature' is a massive, complex dataset. Hence QHS for MTS might seem to be prototypical of the data miner's lament: 'Here's some data we have.. . can you find something interesting?' Nonetheless, the problem is real and important, and(More)
This talk will focus on our recent work in the identification of related documents from different corpora or discipline areas. The purpose of this work is to help a researcher or program manager to identify fruitful cross-disciplinary research areas. The talk will discuss some preliminary results that have been obtained using a small Science News (around(More)
A streaming data clustering algorithm is presented building upon the density-based self-organizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density(More)
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