ChineseDataset

We present a method for computer- assisted authorship attribution based on character-level n-gram language mod- els. Our approach is based on sim- ple information theoretic principles, and achieves improved performance …...

In current dependency parsing models, con- ventional features (i.e. base features) defined over surface words and part-of-speech tags in a relatively high-dimensional feature space may suffer from the data sparseness …...

This paper proposes a graph-based read- ability assessment method using word coupling. Compared to the state-of-the- art methods such as the readability for- mulae, the word-based and feature-based methods, our …...

AbstractVery recently, some studies on neural dependency parsers have shown advantage over the traditional ones on a wide variety of languages. However, for graph-based neural dependency parsing systems, they either …...

AbstractWhile joint models have been developed for many NLP tasks, the vast majority of event coreference resolvers, including the top-performing resolvers competing in the recent TAC KBP 2016 Event Nugget …...

AbstractIn this paper, we present a method which learns the word embedding for readability assessment. For the existing word embedding models, they typically focus on the syntactic or semantic relations …...

AbstractMedical dialogue systems are promising in assisting in telemedicine to increase access to healthcare services, improve the quality of patient care, and reduce medical costs. To facilitate the research and …...

AbstractCant is important for understanding advertising, comedies and dog-whistle politics. However, computational research on cant is hindered by a lack of available datasets. In this paper, we propose a large …...

AbstractOpinion Role Labeling (ORL), aiming to identify the key roles of opinion, has received increasing interest. Unlike most of the previous works focusing on the English language, in this paper, …...

AbstractThis paper presents a novel task to generate poll questions for social media posts. It offers an easy way to hear the voice from the public and learn from their …...

AbstractDespite achieving remarkable performance, previous knowledge-enhanced works usually only use a single-source homogeneous knowledge base of limited knowledge coverage. Thus, they often degenerate into traditional methods because not all dialogues …...

AbstractDependency trees have been intensively used with graph neural networks for aspect-based sentiment classification. Though being effective, such methods rely on external dependency parsers, which can be unavailable for low-resource …...

AbstractThe task of modal dependency parsing aims to parse a text into its modal dependency structure, which is a representation for the factuality of events in the text. We design …...

AbstractThe definition generation task can help language learners by providing explanations for unfamiliar words. This task has attracted much attention in recent years. We propose a novel task of Simple …...

Recent studies in automatic readability assess- ment have shown that hybrid models — mod- els that leverage both linguistically motivated features and neural models — can outperform neural models. However, …...

Abstract“Entity relation extraction, as a core task of information extraction, aims to predict the relation ofentity pairs identified by text, and its research results are applied to various fields. To …...