17,489 research outputs found

    Context-aware Path Ranking for Knowledge Base Completion

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    Knowledge base (KB) completion aims to infer missing facts from existing ones in a KB. Among various approaches, path ranking (PR) algorithms have received increasing attention in recent years. PR algorithms enumerate paths between entity pairs in a KB and use those paths as features to train a model for missing fact prediction. Due to their good performances and high model interpretability, several methods have been proposed. However, most existing methods suffer from scalability (high RAM consumption) and feature explosion (trains on an exponentially large number of features) problems. This paper proposes a Context-aware Path Ranking (C-PR) algorithm to solve these problems by introducing a selective path exploration strategy. C-PR learns global semantics of entities in the KB using word embedding and leverages the knowledge of entity semantics to enumerate contextually relevant paths using bidirectional random walk. Experimental results on three large KBs show that the path features (fewer in number) discovered by C-PR not only improve predictive performance but also are more interpretable than existing baselines

    New Ωc0\Omega_c^0 baryons discovered by LHCb as the members of 1P1P and 2S2S states

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    Inspired by the newly observed Ωc0\Omega_c^0 states at LHCb, we decode their properties by performing an analysis of mass spectrum and decay behavior. Our studies show that the five narrow states, i.e., Ωc(3000)0\Omega_c(3000)^0, Ωc(3050)0\Omega_c(3050)^0, Ωc(3066)0\Omega_c(3066)^0, Ωc(3090)0\Omega_c(3090)^0, and Ωc(3119)0\Omega_c(3119)^0, could be grouped into the 1P1P states with negative parity. Among them, the Ωc(3000)0\Omega_c(3000)^0 and Ωc(3090)0\Omega_c(3090)^0 states could be the JP=1/2J^P=1/2^- candidates, while Ωc(3050)0\Omega_c(3050)^0 and Ωc(3119)0\Omega_c(3119)^0 are suggested as the JP=3/2J^P=3/2^- states. Ωc(3066)0\Omega_c(3066)^0 could be regarded as a JP=5/2J^P=5/2^- state. Since the the spin-parity, the electromagnetic transitions, and the possible hadronic decay channels Ωc()π\Omega_c^{(\ast)}\pi have not been measured yet, other explanations are also probable for these narrow Ωc0\Omega_c^0 states. Additionally, we discuss the possibility of the broad structure Ωc(3188)0\Omega_c(3188)^0 as a 2S2S state with JP=1/2+J^P=1/2^+ or JP=3/2+J^P=3/2^+. In our scheme, Ωc(3119)0\Omega_c(3119)^0 cannot be a 2S2S candidate.Comment: 10 pages, 3 figures, 5 tables, typos corrected. Published in Phys. Rev.

    An End-to-End Trainable Neural Network Model with Belief Tracking for Task-Oriented Dialog

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    We present a novel end-to-end trainable neural network model for task-oriented dialog systems. The model is able to track dialog state, issue API calls to knowledge base (KB), and incorporate structured KB query results into system responses to successfully complete task-oriented dialogs. The proposed model produces well-structured system responses by jointly learning belief tracking and KB result processing conditioning on the dialog history. We evaluate the model in a restaurant search domain using a dataset that is converted from the second Dialog State Tracking Challenge (DSTC2) corpus. Experiment results show that the proposed model can robustly track dialog state given the dialog history. Moreover, our model demonstrates promising results in producing appropriate system responses, outperforming prior end-to-end trainable neural network models using per-response accuracy evaluation metrics.Comment: Published at Interspeech 201