Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Extractive approach for text summarisation using graphs   Natural language processing is an important discipline with the aim of
understanding text by its digital representation, that due to the diverse way
we write and speak, is often not accurate enough. Our paper explores different
graph-related algorithms that can be used in solving the text summarization
problem using an extractive approach. We consider two metrics: sentence overlap
and edit distance for measuring sentence similarity.

18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
36
The categories of this paper are: cmp-lg
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn