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Remembering the Probabilistic Analysis of Latent Semantic Indexing

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Remembering the Probabilistic Analysis of Latent Semantic Indexing
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155
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CC Attribution 3.0 Germany:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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In the late 1990s, the possibility of algorithmic extraction of insight from soulless data loomed potentially important and very intriguing. I will look back at our attempt at understanding and advancing this research program in the light of two decades of blistering progress in spectral methods, machine learning, data harvesting and deep nets.