Identifying Reply-to Relation in Textual Group Chat using Unlabeled Dialogue Scripts and Next Sentence Prediction-Reference-Cited by-同舟云学术

Identifying Reply-to Relation in Textual Group Chat using Unlabeled Dialogue Scripts and Next Sentence Prediction

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Technologies and Applications of Artificial Intelligence (TAAI)
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Author:

Shan Junjie¹,Nishihara Yoko²,Han Yihong³

Affiliation:

1. Ritsumeikan Global Innovation Research Organization, Ritsumeikan University,Kusatsu,Japan

2. College of Information Science and Engineering, Ritsumeikan University,Kusatsu,Japan

3. Graduate School of Information Science and Engineering, Ritsumeikan University,Kusatsu,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10056427/10056431/10056443.pdf?arnumber=10056443

Reference14 articles.

1. Who is answering whom? Finding “Reply-To” relations in group chats with deep bidirectional LSTM networks

2. Chat disentanglement: Identifying semantic reply relationships with random forests and recurrent neural networks;mehri;Proceedings of the Eighth International Joint Conference on Natural Language Processing,0

3. Question Generation for Reading Comprehension Test Complying with Types of Question;shan;Journal of Information Science and Engineering,2022

4. Optimized combinatorial clustering for stochastic processes

5. Context-based message expansion for disentanglement of interleaved text conversations

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