Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching-Reference-Cited by-同舟云学术

Multi-modal Attentive Graph Pooling Model for Community Question Answer Matching

Published:2020-10-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM International Conference on Multimedia
language:
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Author:

Hu Jun¹,Fang Quan²,Qian Shengsheng²,Xu Changsheng³

Affiliation:

1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

2. Institute of Automation, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

3. Institute of Automation, Chinese Academy of Sciences & University of Chinese Academy of Sciences; Peng Cheng Laboratory, Beijing, China

Funder

National Natural Science Foundation of China under Grants

Key Research Program of Frontier Sciences, CAS

K.C.Wong Education Foundation

National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3394171.3413711

Reference40 articles.

1. Graph Convolutional Encoders for Syntax-aware Neural Machine Translation

2. From text question-answering to multimedia QA on web-scale media resources

3. metapath2vec

4. Hanyin Fang Fei Wu Zhou Zhao Xinyu Duan Yueting Zhuang and Martin Ester. 2016a. Community-Based Question Answering via Heterogeneous Social Network Learning. In AAAI. AAAI Press 122--128. Hanyin Fang Fei Wu Zhou Zhao Xinyu Duan Yueting Zhuang and Martin Ester. 2016a. Community-Based Question Answering via Heterogeneous Social Network Learning. In AAAI. AAAI Press 122--128.

5. Folksonomy-Based Visual Ontology Construction and Its Applications

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