Complex and Holographic Embeddings of Knowledge Graphs: A Comparison

Understand

Embeddings of knowledge graphs have received significant attention due to their excellent performance for tasks like link prediction and entity resolution.

• In this short paper, we are providing a comparison of two state-of-the-art knowledge graph embeddings for which their equivalence has recently been established, i.e., ComplEx and HolE [Nickel, Rosasco, and Poggio, 2016; Trouillon et al., 2016; Hayashi and Shimbo, 2017].
• First, we briefly review both models and discuss how their scoring functions are equivalent.
• We then analyze the discrepancy of results reported in the original articles, and show experimentally that they are likely due to the use of different loss functions.