Tensor Decompositions for temporal knowledge base completion

Most algorithms for representation learning and link prediction in relational data have been designed for static data. However, the data they are applied to usually evolves with time, such as friend graphs in social networks or user interactions with items in recommender systems... (read more)

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Datasets


Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Link Prediction ICEWS05-15 TNTComplEx MRR 0.60 # 3
Link Prediction ICEWS05-15 TNTComplEx (x10) MRR 0.67 # 1
Link Prediction ICEWS14 TNTComplEx (x10) MRR 0.62 # 1
Link Prediction ICEWS14 TNTComplEx MRR 0.56 # 3
Link Prediction YAGO15k TNTComplEx MRR 0.35 # 2
Link Prediction YAGO15k TNTComplEx (x10) MRR 0.37 # 1

Methods used in the Paper


METHOD TYPE
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