Titlebook: Chinese ComputationalLinguistics; 20th China National Sheng Li,Maosong Sun,Gaoqi Rao Conference proceedings 2021 Springer Nature Switzerla

反省

車床

Incorporating Translation Quality Estimation into Chinese-Korean Neural Machine Translationer forcing strategy for training in the NMT models. Moreover, the NMT models usually require the large-scale and high-quality parallel corpus. However, Korean is a low resource language, and there is no large-scale parallel corpus between Chinese and Korean, which is a challenging for the researcher

NEEDY

Emotion Classification of COVID-19 Chinese Microblogs Based on the Emotion Category Descriptionres of the microblog itself, without combining the semantics of emotion categories for modeling. Emotion classification of microblogs is a process of reading the content of microblogs and combining the semantics of emotion categories to understand whether it contains a certain emotion. Inspired by t

persistence

Multi-level Emotion Cause Analysis by Multi-head Attention Based Multi-task Learninghe emotion cause at the clause level. However, in many scenarios, only extracting the cause clause is ambiguous. To ease the problem, in this paper, we introduce multi-level emotion cause analysis, which focuses on identifying emotion cause clause (ECC) and emotion cause keywords (ECK) simultaneousl

遺留之物

Using Query Expansion in Manifold Ranking for Query-Oriented Multi-document Summarizationntences, but also the relationships between the given query and the sentences. However, the information of original query is often insufficient. So we present a query expansion method, which is combined in the manifold ranking to resolve this problem. Our method not only utilizes the information of

寬宏大量

不可磨滅

Incorporating Commonsense Knowledge into Abstractive Dialogue Summarization via Heterogeneous Graph present a novel multi-speaker dialogue summarizer to demonstrate how large-scale commonsense knowledge can facilitate dialogue understanding and summary generation. In detail, we consider utterance and commonsense knowledge as two different types of data and design a Dialogue Heterogeneous Graph Net

NEG

Detonate

Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domainers have specific background knowledge. Therefore, those messages are usually short and lacking in background information, which is different from the text in the other domain. Thus, it is difficult for a machine to understand the messages comprehensively. Fortunately, a key nature of social media i

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