Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Replication of the Keyword Extraction part of the paper "'Without the
  Clutter of Unimportant Words': Descriptive Keyphrases for Text Visualization"   "Keyword Extraction" refers to the task of automatically identifying the most
relevant and informative phrases in natural language text. As we are deluged
with large amounts of text data in many different forms and content - emails,
blogs, tweets, Facebook posts, academic papers, news articles - the task of
"making sense" of all this text by somehow summarizing them into a coherent
structure assumes paramount importance. Keyword extraction - a well-established
problem in Natural Language Processing - can help us here. In this report, we
construct and test three different hypotheses (all related to the task of
keyword extraction) that take us one step closer to understanding how to
meaningfully identify and extract "descriptive" keyphrases. The work reported
here was done as part of replicating the study by Chuang et al. [3].

26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th