Current Chinese event extract ion systems suffer much from the low recall due to unknown triggers. To resolve this problem, this paper firstly introduces morphological structures to better represent the compositional semantics inside Chinese triggers and then proposes a mechanism to automatically identify the head morpheme (either verb or noun) as the governing sememe of a trigger. Finally, it ...

Deep neural networks (DNNs) are known to be vulnerable adversarial images, while their robustness in text classification rarely studied. Several lines of attack methods have been proposed the literature, such as character-level, word-level, and sentence-level attacks. However, it is still a challenge minimize number word distortions necessary induce misclassification, simultaneously ensuring le...

Short texts usually encounter data sparsity and ambiguity problems in representations for their lack of context. In this paper, we propose a novel method to model short texts based on semantic clustering and convolutional neural network. Particularly, we first discover semantic cliques in embedding spaces by a fast clustering algorithm. Then, multi-scale semantic units are detected under the su...

We present a graph-matching algorithm for semantic relation assignment. The algorithm is part of an interactive text analysis system. The system automatically extracts pairs of syntactic units from a text and assigns a semantic relation to each pair. This is an incremental learning algorithm, in which previously processed pairs and user feedback guide the process. After each assignment, the sys...