Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: EntropyDB: A Probabilistic Approach to Approximate Query Processing   We present EntropyDB, an interactive data exploration system that uses a
probabilistic approach to generate a small, query-able summary of a dataset.
Departing from traditional summarization techniques, we use the Principle of
Maximum Entropy to generate a probabilistic representation of the data that can
be used to give approximate query answers. We develop the theoretical framework
and formulation of our probabilistic representation and show how to use it to
answer queries. We then present solving techniques, give two critical
optimizations to improve preprocessing time and query execution time, and
explore methods to reduce query error. Lastly, we experimentally evaluate our
work using a 5 GB dataset of flights within the United States and a 210 GB
dataset from an astronomy particle simulation. While our current work only
supports linear queries, we show that our technique can successfully answer
queries faster than sampling while introducing, on average, no more error than
sampling and can better distinguish between rare and nonexistent values. We
also discuss extensions that can allow for data updates and linear queries over
joins.

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The categories of this paper are: mtrl-th
20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
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The categories of this paper are: alg-geom
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The categories of this paper are: plasm-ph
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
22
The categories of this paper are: chao-dyn
14
The categories of this paper are: math-ph
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The categories of this paper are: supr-con
29
The categories of this paper are: funct-an
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The categories of this paper are: hep-lat
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat