Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficiently Embedding Dynamic Knowledge Graphs   Knowledge graph (KG) embedding encodes the entities and relations from a KG
into low-dimensional vector spaces to support various applications such as KG
completion, question answering, and recommender systems. In real world,
knowledge graphs (KGs) are dynamic and evolve over time with addition or
deletion of triples. However, most existing models focus on embedding static
KGs while neglecting dynamics. To adapt to the changes in a KG, these models
need to be re-trained on the whole KG with a high time cost.
  In this paper, to tackle the aforementioned problem, we propose a new
context-aware Dynamic Knowledge Graph Embedding (DKGE) method which supports
the embedding learning in an online fashion. DKGE introduces two different
representations (i.e., knowledge embedding and contextual element embedding)
for each entity and each relation, in the joint modeling of entities and
relations as well as their contexts, by employing two attentive graph
convolutional networks, a gate strategy, and translation operations. This
effectively helps limit the impacts of a KG update in certain regions, not in
the entire graph, so that DKGE can rapidly acquire the updated KG embedding by
a proposed online learning algorithm. Furthermore, DKGE can also learn KG
embedding from scratch. Experiments on the tasks of link prediction and
question answering in a dynamic environment demonstrate the effectiveness and
efficiency of DKGE.

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The categories of this paper are: mtrl-th
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The categories of this paper are: ao-sci
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The categories of this paper are: q-bio
3
The categories of this paper are: physics
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The categories of this paper are: cmp-lg
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The categories of this paper are: econ
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The categories of this paper are: atom-ph
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The categories of this paper are: q-alg
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The categories of this paper are: hep-th
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The categories of this paper are: funct-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: nucl-th
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The categories of this paper are: chem-ph