Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Tackling scalability issues in mining path patterns from knowledge
  graphs: a preliminary study   Features mined from knowledge graphs are widely used within multiple
knowledge discovery tasks such as classification or fact-checking. Here, we
consider a given set of vertices, called seed vertices, and focus on mining
their associated neighboring vertices, paths, and, more generally, path
patterns that involve classes of ontologies linked with knowledge graphs. Due
to the combinatorial nature and the increasing size of real-world knowledge
graphs, the task of mining these patterns immediately entails scalability
issues. In this paper, we address these issues by proposing a pattern mining
approach that relies on a set of constraints (e.g., support or degree
thresholds) and the monotonicity property. As our motivation comes from the
mining of real-world knowledge graphs, we illustrate our approach with PGxLOD,
a biomedical knowledge graph.

35
The categories of this paper are: mtrl-th
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
33
The categories of this paper are: plasm-ph
30
The categories of this paper are: q-alg
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
13
The categories of this paper are: quant-ph