Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Generalized Method for Integrating Rule-based Knowledge into Inductive
  Methods Through Virtual Sample Creation   Hybrid learning methods use theoretical knowledge of a domain and a set of
classified examples to develop a method for classification. Methods that use
domain knowledge have been shown to perform better than inductive learners.
However, there is no general method to include domain knowledge into all
inductive learning algorithms as all hybrid methods are highly specialized for
a particular algorithm. We present an algorithm that will take domain knowledge
in the form of propositional rules, generate artificial examples from the rules
and also remove instances likely to be flawed. This enriched dataset then can
be used by any learning algorithm. Experimental results of different scenarios
are shown that demonstrate this method to be more effective than simple
inductive learning.

24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an