

<?xml version="1.0" encoding="UTF-8"?>
<record>
  <title>An improved K-means algorithm application in evaluating interactive mechanism of airline industry ecosystem stability</title>
  <journal>Journal of Digital Information Management</journal>
  <author>Qing Liu</author>
  <volume>15</volume>
  <issue>4</issue>
  <year>2017</year>
  <doi></doi>
  <url>http://dline.info/fpaper/jdim/v15i4/jdimv15i4_4.pdf</url>
  <abstract>With the explosive growth of the mass data,
the traditional architecture of the information system has
been difficult to deal with enterprise needs. Data mining
has become an important means of business innovation;
it changed the development direction of cloud computing
and also lead software-as-a-service (SaaS) becomes the
main indicator of the era of cloud 2.0. This paper proposed
an improved K-means algorithm, and uses it to evaluate
interactive mechanism of airline industry ecosystem
stability. Aiming at the clustering instability problem of
traditional K-means algorithm in the process of random
selection, this paper proposes a stochastic selection
method for clustering centers initialization, the efficiency
of the algorithm also has been greatly improved. By using
data mining method, we make analysis of the ecological
stability system of aviation industry; the result shows that
technological innovation is the source of system stability,
so it is the key link to the stability of the industrial
ecosystem.</abstract>
</record>
