PlanetAlign.algorithms.DualMatch

class DualMatch(dtype: dtype = torch.float32)[source]

Bases: BaseModel

Embedding-based method DualMatch for pairwise unsupervised entity alignment. DualMatch is proposed by the paper “Unsupervised Entity Alignment for Temporal Knowledge Graphs” in WWW 2023.

test(dataset: Dataset, gids: List[int] | Tuple[int, ...], metrics: tuple[str] | list[str] = None)
Parameters:

  • dataset (Dataset) – The dataset containing the graphs to be aligned and the training/test data.

  • gids (list[int] or tuple[int, ...]) – The indices of the graphs in the dataset to be aligned.

  • metrics (tuple[str] or list[str], optional) – The metrics to be computed after alignment. Default is None, which computes Hits@K (K=1, 10, 30, 50) and MRR metrics.