Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Retrieving and ranking short medical questions with two stages neural
  matching model   Internet hospital is a rising business thanks to recent advances in mobile
web technology and high demand of health care services. Online medical services
become increasingly popular and active. According to US data in 2018, 80
percent of internet users have asked health-related questions online. Numerous
data is generated in unprecedented speed and scale. Those representative
questions and answers in medical fields are valuable raw data sources for
medical data mining. Automated machine interpretation on those sheer amount of
data gives an opportunity to assist doctors to answer frequently asked
medical-related questions from the perspective of information retrieval and
machine learning approaches. In this work, we propose a novel two-stage
framework for the semantic matching of query-level medical questions.

15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex