Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Zap: Making Predictions Based on Online User Behavior   This paper introduces Zap, a generic machine learning pipeline for making
predictions based on online user behavior. Zap combines well known techniques
for processing sequential data with more obscure techniques such as Bloom
filters, bucketing, and model calibration into an end-to-end solution. The
pipeline creates website- and task-specific models without knowing anything
about the structure of the website. It is designed to minimize the amount of
website-specific code, which is realized by factoring all website-specific
logic into example generators. New example generators can typically be written
up in a few lines of code.

30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
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The categories of this paper are: comp-gas
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The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th