Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

Reasoning is essential for the development of large knowledge graphs, especially for completion, which aims to infer new triples based on existing ones. Both rules and embeddings can be used for knowledge graph reasoning and they have their own advantages and difficulties. Rule-based reasoning is accurate and explainable but rule learning with searching over the graph always suffers from efficiency due to huge search space. Embedding-based reasoning is more scalable and efficient as the reasoning is conducted via computation between embeddings, but it has difficulty learning good representations for sparse entities because a good embedding relies heavily on data richness. Based on this observation, in this paper we explore how embedding and rule learning can be combined together and complement each other's difficulties with their advantages. We propose a novel framework IterE iteratively learning embeddings and rules, in which rules are learned from embeddings with proper pruning strategy and embeddings are learned from existing triples and new triples inferred by rules. Evaluations on embedding qualities of IterE show that rules help improve the quality of sparse entity embeddings and their link prediction results. We also evaluate the efficiency of rule learning and quality of rules from IterE compared with AMIE+, showing that IterE is capable of generating high quality rules more efficiently. Experiments show that iteratively learning embeddings and rules benefit each other during learning and prediction.Comment: This paper is accepted by WWW'1

Top quark decays with flavor violation in the B-LSSM

The decays of top quark $t\rightarrow c\gamma,\;t\rightarrow cg,\;t\rightarrow cZ,\;t\rightarrow ch$ are extremely rare processes in the standard model (SM). The predictions on the corresponding branching ratios in the SM are too small to be detected in the future, hence any measurable signal for the processes at the LHC is a smoking gun for new physics. In the extension of minimal supersymmetric standard model with an additional local $U(1)_{B-L}$ gauge symmetry (B-LSSM), new gauge interaction and new flavor changing interaction affect the theoretical evaluations on corresponding branching ratios of those processes. In this work, we analyze those processes in the B-LSSM, under a minimal flavor violating assumption for the soft breaking terms. Considering the constraints from updated experimental data, the numerical results imply $Br(t\rightarrow c\gamma)\sim5\times10^{-7}$, $Br(t\rightarrow cg)\sim2\times10^{-6}$, $Br(t\rightarrow cZ)\sim4\times10^{-7}$ and $Br(t\rightarrow ch)\sim3\times10^{-9}$ in our chosen parameter space. Simultaneously, new gauge coupling constants $g_{_B},\;g_{_{YB}}$ in the B-LSSM can also affect the numerical results of $Br(t\rightarrow c\gamma,\;cg,\;cZ,\;ch)$.Comment: 20 pages, 4 figures, published in EPJC. arXiv admin note: substantial text overlap with arXiv:1803.0990