Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Attempt to Predict Failure Case Classification in a Failure Database by
  using Neural Network Models   With the recent progress of information technology, the use of networked
information systems has rapidly expanded. Electronic commerce and electronic
payments between banks and companies, and online shopping and social networking
services used by the general public are examples of such systems. Therefore, in
order to maintain and improve the dependability of these systems, we are
constructing a failure database from past failure cases. When importing new
failure cases to the database, it is necessary to classify these cases
according to failure type. The problems are the accuracy and efficiency of the
classification. Especially when working with multiple individuals, unification
of classification is required. Therefore, we are attempting to automate
classification using machine learning. As evaluation models, we selected the
multilayer perceptron (MLP), the convolutional neural network (CNN), and the
recurrent neural network (RNN), which are models that use neural networks. As a
result, the optimal model in terms of accuracy is first the MLP followed by the
CNN, and the processing time of the classification is practical.

19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
15
The categories of this paper are: nucl-ex
30
The categories of this paper are: q-alg
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc