Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comparison Between Traditional Machine Learning Models And Neural
  Network Models For Vietnamese Hate Speech Detection   Hate-speech detection on social network language has become one of the main
researching fields recently due to the spreading of social networks like
Facebook and Twitter. In Vietnam, the threat of offensive and harassment cause
bad impacts for online user. The VLSP - Shared task about Hate Speech Detection
on social networks showed many proposed approaches for detecting whatever
comment is clean or not. However, this problem still needs further researching.
Consequently, we compare traditional machine learning and deep learning on a
large dataset about the user's comments on social network in Vietnamese and
find out what is the advantage and disadvantage of each model by comparing
their accuracy on F1-score, then we pick two models in which has highest
accuracy in traditional machine learning models and deep neural models
respectively. Next, we compare these two models capable of predicting the right
label by referencing their confusion matrices and considering the advantages
and disadvantages of each model. Finally, from the comparison result, we
propose our ensemble method that concentrates the abilities of traditional
methods and deep learning methods.

33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas