Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Text Classification for Azerbaijani Language Using Machine Learning and
  Embedding   Text classification systems will help to solve the text clustering problem in
the Azerbaijani language. There are some text-classification applications for
foreign languages, but we tried to build a newly developed system to solve this
problem for the Azerbaijani language. Firstly, we tried to find out potential
practice areas. The system will be useful in a lot of areas. It will be mostly
used in news feed categorization. News websites can automatically categorize
news into classes such as sports, business, education, science, etc. The system
is also used in sentiment analysis for product reviews. For example, the
company shares a photo of a new product on Facebook and the company receives a
thousand comments for new products. The systems classify the comments into
categories like positive or negative. The system can also be applied in
recommended systems, spam filtering, etc. Various machine learning techniques
such as Naive Bayes, SVM, Decision Trees have been devised to solve the text
classification problem in Azerbaijani language.

36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
19
The categories of this paper are: eess
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph