Semantic similarity-based program retrieval: a multi-relational graph perspective

Qianwen Gou

doi:10.1007/s11704-023-2678-8

2023-12-13

PRE

DOI：10.1007/s11704-023-2678-8

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摘要

En 中文

ConclusionIn this paper, we formulate the program retrieval problem as a graph similarity problem. This is achieved by first explicitly representing queries and program snippets as AMR and CPG, respectively. Then, through intra-level and inter-level attention mechanisms to infer fine-grained correspondence by propagating node correspondence along the graph edge. Moreover, such a design can learn correspondence of nodes at different levels, which were mostly ignored by previous works. Experiments have demonstrated the superiority of USRAE.

期刊

Frontiers of Computer Science

IF:

4.6

论文数:

1.6K

被引数:

2.8K

机构

Northwestern Polytechnical University

学者数:

4.6W

论文数: 3.7W

被引数: 5.3W

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