Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Topological Feature Based Classification   There has been a lot of interest in developing algorithms to extract clusters
or communities from networks. This work proposes a method, based on
blockmodelling, for leveraging communities and other topological features for
use in a predictive classification task. Motivated by the issues faced by the
field of community detection and inspired by recent advances in Bayesian topic
modelling, the presented model automatically discovers topological features
relevant to a given classification task. In this way, rather than attempting to
identify some universal best set of clusters for an undefined goal, the aim is
to find the best set of clusters for a particular purpose.
  Using this method, topological features can be validated and assessed within
a given context by their predictive performance.
  The proposed model differs from other relational and semi-supervised learning
models as it identifies topological features to explain the classification
decision. In a demonstration on a number of real networks the predictive
capability of the topological features are shown to rival the performance of
content based relational learners. Additionally, the model is shown to
outperform graph-based semi-supervised methods on directed and approximately
bipartite networks.

35
The categories of this paper are: mtrl-th
8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci