Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Profit Maximization Auction and Data Management in Big Data Markets   A big data service is any data-originated resource that is offered over the
Internet. The performance of a big data service depends on the data bought from
the data collectors. However, the problem of optimal pricing and data
allocation in big data services is not well-studied. In this paper, we propose
an auction-based big data market model. We first define the data cost and
utility based on the impact of data size on the performance of big data
analytics, e.g., machine learning algorithms. The big data services are
considered as digital goods and uniquely characterized with "unlimited supply"
compared to conventional goods which are limited. We therefore propose a
Bayesian profit maximization auction which is truthful, rational, and
computationally efficient. The optimal service price and data size are obtained
by solving the profit maximization auction. Finally, experimental results on a
real-world taxi trip dataset show that our big data market model and auction
mechanism effectively solve the profit maximization problem of the service
provider.

36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org