Titlebook: Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding; Third China Conferen Jun Zhao,Frank van Harmelen,Xi

柔声地说

Convolutional Neural Network-Based Question Answering Over Knowledge Base with Type Constraint,g, our method relies on various components for solving different sub-tasks of the problem. In the first stage, we directly use the result of entity linking to obtain the topic entity in a question, and simplify the process as a semantic matching problem. We train a neural network to match questions

灌输

SIT

Constrain

DSKG: A Deep Sequential Model for Knowledge Graph Completion,ompletion models compel two-thirds of a triple provided (e.g., . and .) to predict the remaining one. In this paper, we propose a new model, which uses a KG-specific multi-layer recurrent neutral network (RNN) to model triples in a KG as sequences. It outperformed several state-of-the-art KG complet

河潭

Pattern Learning for Chinese Open Information Extraction, OIE. However, few studies have been reported on OIE for languages beyond English. This paper presents a Chinese OIE system PLCOIE to extract binary relation triples and N-ary relation tuples from Chinese documents. Our goal is to learn general patterns that is composed of both dependency parsing ro

adequate-intake

Adversarial Training for Relation Classification with Attention Based Gate Mechanism,owever, existing neural networks for relation classification heavily rely on the quality of labelled data and tend to be overconfident about the noise in input signals. They may be limited in robustness and generalization. In this paper, we apply adversarial training to the relation classification b

Silent-Ischemia

A Novel Approach on Entity Linking for Encyclopedia Infoboxes, construction. However, if the hyperlink is missing in the Infobox, the semantic relatedness cannot be created. In this paper, we propose an effective model and summarize the most possible features for the infobox entity linking problem. Empirical studies confirm the superiority of our proposed mode

昆虫

百科全书

Knowledge Augmented Inference Network for Natural Language Inference,models on Natural Language Inference (NLI) task. Different from previous works that use one-hot representations to describe external knowledge, we employ the TransE model to encode various semantic relations extracted from the external Knowledge Base (KB) as distributed relation features. We utilize

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