Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bringing Salary Transparency to the World: Computing Robust Compensation
  Insights via LinkedIn Salary   The recently launched LinkedIn Salary product has been designed with the goal
of providing compensation insights to the world's professionals and thereby
helping them optimize their earning potential. We describe the overall design
and architecture of the statistical modeling system underlying this product. We
focus on the unique data mining challenges while designing and implementing the
system, and describe the modeling components such as Bayesian hierarchical
smoothing that help to compute and present robust compensation insights to
users. We report on extensive evaluation with nearly one year of de-identified
compensation data collected from over one million LinkedIn users, thereby
demonstrating the efficacy of the statistical models. We also highlight the
lessons learned through the deployment of our system at LinkedIn.

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The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
12
The categories of this paper are: nucl-th
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
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The categories of this paper are: eess
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc