Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating Node Importance in Knowledge Graphs Using Graph Neural
  Networks   How can we estimate the importance of nodes in a knowledge graph (KG)? A KG
is a multi-relational graph that has proven valuable for many tasks including
question answering and semantic search. In this paper, we present GENI, a
method for tackling the problem of estimating node importance in KGs, which
enables several downstream applications such as item recommendation and
resource allocation. While a number of approaches have been developed to
address this problem for general graphs, they do not fully utilize information
available in KGs, or lack flexibility needed to model complex relationship
between entities and their importance. To address these limitations, we explore
supervised machine learning algorithms. In particular, building upon recent
advancement of graph neural networks (GNNs), we develop GENI, a GNN-based
method designed to deal with distinctive challenges involved with predicting
node importance in KGs. Our method performs an aggregation of importance scores
instead of aggregating node embeddings via predicate-aware attention mechanism
and flexible centrality adjustment. In our evaluation of GENI and existing
methods on predicting node importance in real-world KGs with different
characteristics, GENI achieves 5-17% higher NDCG@100 than the state of the art.

18
The categories of this paper are: econ
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex