Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Augmenting Knowledge Graphs for Better Link Prediction   Embedding methods have demonstrated robust performance on the task of link
prediction in knowledge graphs, by mostly encoding entity relationships. Recent
methods propose to enhance the loss function with a literal-aware term. In this
paper, we propose KGA: a knowledge graph augmentation method that incorporates
literals in an embedding model without modifying its loss function. KGA
discretizes quantity and year values into bins, and chains these bins both
horizontally, modeling neighboring values, and vertically, modeling multiple
levels of granularity. KGA is scalable and can be used as a pre-processing step
for any existing knowledge graph embedding model. Experiments on legacy
benchmarks and a new large benchmark, DWD, show that augmenting the knowledge
graph with quantities and years is beneficial for predicting both entities and
numbers, as KGA outperforms the vanilla models and other relevant baselines.
Our ablation studies confirm that both quantities and years contribute to KGA's
performance, and that its performance depends on the discretization and binning
settings. We make the code, models, and the DWD benchmark publicly available to
facilitate reproducibility and future research.

11
The categories of this paper are: hep-lat
10
The categories of this paper are: q-bio
6
The categories of this paper are: astro-ph
2
The categories of this paper are: math
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
17
The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con