Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Evaluating topic coherence measures   Topic models extract representative word sets - called topics - from word
counts in documents without requiring any semantic annotations. Topics are not
guaranteed to be well interpretable, therefore, coherence measures have been
proposed to distinguish between good and bad topics. Studies of topic coherence
so far are limited to measures that score pairs of individual words. For the
first time, we include coherence measures from scientific philosophy that score
pairs of more complex word subsets and apply them to topic scoring.

22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph