Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Customers Behavior Modeling by Semi-Supervised Learning in Customer
  Relationship Management   Leveraging the power of increasing amounts of data to analyze customer base
for attracting and retaining the most valuable customers is a major problem
facing companies in this information age. Data mining technologies extract
hidden information and knowledge from large data stored in databases or data
warehouses, thereby supporting the corporate decision making process. CRM uses
data mining (one of the elements of CRM) techniques to interact with customers.
This study investigates the use of a technique, semi-supervised learning, for
the management and analysis of customer-related data warehouse and information.
The idea of semi-supervised learning is to learn not only from the labeled
training data, but to exploit also the structural information in additionally
available unlabeled data. The proposed semi-supervised method is a model by
means of a feed-forward neural network trained by a back propagation algorithm
(multi-layer perceptron) in order to predict the category of an unknown
customer (potential customers). In addition, this technique can be used with
Rapid Miner tools for both labeled and unlabeled data.

17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
23
The categories of this paper are: solv-int
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex