Papers by Jianchao Zhu

2 papers
An Effective and Efficient Entity Alignment Decoding Algorithm via Third-Order Tensor Isomorphism (2022.acl-long)

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Challenge: Existing methods focus on graph representation learning, but decoding is a key part of the process.
Approach: They propose an EA Decoding Algorithm via Third-order Tensor Isomorphism (DATTI) they combine two sets of isomorphic equations to enhance the decoding process .
Outcome: The proposed algorithm can deliver significant performance improvements even on the most advanced methods while the extra required time is less than 3 seconds.
A Simple Temporal Information Matching Mechanism for Entity Alignment between Temporal Knowledge Graphs (2022.coling-1)

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Challenge: Existing methods for EA between temporal KGs incorporate relational and temporal information into entity embeddings.
Approach: They propose a method to generate unsupervised alignment seeds using temporal information from TKGs.
Outcome: The proposed method outperforms the previous methods by using temporal information.

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