Inductive Link Prediction for Nodes Having Only Attribute Information
- URL: http://arxiv.org/abs/2007.08053v1
- Date: Thu, 16 Jul 2020 00:51:51 GMT
- Title: Inductive Link Prediction for Nodes Having Only Attribute Information
- Authors: Yu Hao, Xin Cao, Yixiang Fang, Xike Xie, Sibo Wang
- Abstract summary: In attributed graphs, both the structure and attribute information can be utilized for link prediction.
We propose a model called DEAL, which consists of three components: two node embedding encoders and one alignment mechanism.
Our proposed model significantly outperforms existing inductive link prediction methods, and also outperforms the state-of-the-art methods on transductive link prediction.
- Score: 21.714834749122137
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Predicting the link between two nodes is a fundamental problem for graph data
analytics. In attributed graphs, both the structure and attribute information
can be utilized for link prediction. Most existing studies focus on
transductive link prediction where both nodes are already in the graph.
However, many real-world applications require inductive prediction for new
nodes having only attribute information. It is more challenging since the new
nodes do not have structure information and cannot be seen during the model
training. To solve this problem, we propose a model called DEAL, which consists
of three components: two node embedding encoders and one alignment mechanism.
The two encoders aim to output the attribute-oriented node embedding and the
structure-oriented node embedding, and the alignment mechanism aligns the two
types of embeddings to build the connections between the attributes and links.
Our model DEAL is versatile in the sense that it works for both inductive and
transductive link prediction. Extensive experiments on several benchmark
datasets show that our proposed model significantly outperforms existing
inductive link prediction methods, and also outperforms the state-of-the-art
methods on transductive link prediction.
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