本論文擴展進行文本一般性摘要的指標生成網路，建構一個給定查詢詞為輸入型式的查詢式摘要系統。本論文所提出模型以查詢詞標籤輔助從文本學習到查詢詞相關語意，並設計句意混合單元加強模型對句子層級語意的理解，用以有效生成與查詢詞相關的摘要結果。此外，以監督式學習的查詢式摘要生成系統需要足夠多的 <文本，查詢詞，查詢摘要> 資料進行模型訓練，但人工標示成本極高而不易取得。因此本論文提供一個自動化方法，根據語法分析從現有一般性摘要資料集轉換成查詢式摘要資料集的形式，以提供模型建構及測試用。實驗結果顯示本論文由CNN/Dailymail轉換產生的查詢式摘要資料集較相關研究能提供模型更好的訓練效果。且本論文所提查詢詞標籤輔助的查詢式摘要生成模型，能有效解決查詢詞為系統未知語意字彙而影響摘要生成效能的問題，並透過句意混和單元提升模型生成結果與查詢詞內容相關的精確度。

[1] Çaglar Gülçehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, and Yoshua Bengio. 2016. Pointing the unknown words. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Berlin, Germany, pages 140–149.
[2] Johan Hasselqvist, Niklas Helmertz, and Mikael Kågebäck. 2017. Query-Based Abstractive Summarization Using Neural Networks. CoRR abs/1712.06100 (2017).
[3] Julian Kupiec, Jan Pedersen, and Francine Chen. 1995. A trainable document summarizer. In International ACM SIGIR conference on Research and development in information retrieval.
[4] Chris D Paice. 1990. Constructing literature abstracts by computer: techniques and prospects. Information Processing & Management 26(1):171–186.
[5] Horacio Saggion and Thierry Poibeau. 2013. Automatic text summarization: Past, present and future. In Multi-source, Multilingual Information Extraction and Summarization, Springer, pages 3–21.
[6] Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014. Sequence to sequence learning with neural networks. In Neural Information Processing Systems.
[7] Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. 2016. Modeling coverage for neural machine translation. In ACL 2016
[8] Preksha Nema, Mitesh Khapra, Anirban Laha, and Balaraman Ravindran. 2017. Diversity driven Attention Model for Query-based Abstractive Summarization. In ACL 2017
[9] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. International Conference on Learning Representations (ICLR 2015) arXiv:1409.0473.
[10] Abigail See, Peter J. Liu, and Christopher D. Manning. 2017. Get To The Point: Summarization with Pointer-Generator Networks. In ACL 2017
[11] Nallapati, R., Zhai, F., and Zhou, B. (2017). Summarunner: A recurrent neural network based sequence model for extractive summarization of documents.In AAAI 2017.
[12] Sutskever, I., Vinyals, O., and Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems, pages 3104–3112.
[13] Cho, K., Van Merri¨enboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., and Bengio, Y. (2014). Learning phrase representations using rnn encoderdecoder for statistical machine translation. In EMNLP 2014.
[14] Rush, A. M., Chopra, S., and Weston, J. (2015). A neural attention model for abstractive sentence summarization. In EMNLP 2015.
[15] Angela Fan, David Grangier, Michael Auli .(2018) . Controllable Abstractive Summarization . ACL2018 Workshop on Neural Machine Translation and Generation (NMT@ACL)
[16] Tatsuya Ishigaki, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen and Manabu OkumuraNeural .Query-Based Abstractive Summarization Using Copying Mechanism. ECIR2020
[17] Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, Phil Blunsom .Teaching Machines to Read and Comprehend. NIPS2015
[18] Dragomir Radev, Timothy Allison, Sasha Blair Goldensohn, John Blitzer, Arda Celebi, Stanko Dimitrov, Elliott Drabek, Ali Hakim, Wai Lam, Danyu Liu, et al. 2004. Mead-a platform for multidocument multilingual text summarization. Tech-nicalreport, Columbia University Academic Commons.
[19] G¨unes¸ Erkan and Dragomir R. Radev. 2004. Lexpagerank: Prestige in multi-document text summarization. 2004 EMNLP,
[20] Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. BLEU: a Method for Automatic Evaluation of Machine Translation. 2002 ACL
[21] Chin-Yew Lin. 2004. ROUGE: A Package for Automatic Evaluation of Summar-ies. 2004 ACL