PPT-A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss

1 WanTing Hsu National Tsing Hua University Chieh Kai Lin National Tsing Hua University Project page Outline Motivation Our Method Training Procedures Experiments and Results Conclusion. (published at ESEC/FSE’09). Yingfei Xiong. Ph.D., University of Tokyo. Will be a postdoc@Univ. Waterloo since Dec. Joint work with. Zhenjiang Hu, Haiyan Zhao, Hui Song, . Masato Takeichi, and Hong Mei. John . Cadigan. , David Ellison, and Ethan Roday. Approach. Preprocessing and data cleanup. Vectorization. K-means . Information ordering with the experts system. CLASSY-style content realization. Raw Input . (published at ESEC/FSE’09). Yingfei Xiong. Ph.D., University of Tokyo. Will be a postdoc@Univ. Waterloo since Dec. Joint work with. Zhenjiang Hu, Haiyan Zhao, Hui Song, . Masato Takeichi, and Hong Mei. Overview. Ling573. Systems & Applications. March 31. , 2016. Roadmap. Dimensions . of the problem. Architecture . of a Summarization system. Summarization and resources. Evaluation. Logistics Check-. Reviews & Speech. Ling 573. Systems and Applications. May . 26, 2016. Roadmap. Abstractive summarization example. Using Abstract Meaning Representation. Review . summarization:. Basic approach. Learning what users want. Yingfei . Xiong. University of Tokyo, Japan. Zhenjiang Hu. National Institute of Informatics, Japa. n. Haiyan. Zhao. Peking University,. China. Hui. Song. Peking University,. China. Masato Takeichi. (Combined Method). 1. Tatsuro. . Oya. Extractive Summarization DA Recognition. . Locate . important sentences . in email and model . dialogue . acts . simultaneously. .. 2. Outline. Introduction. Access Pipeline Protests (NoDAPL). CS 5984/4984 Big Data Text Summarization Report. . Xiaoyu Chen*, Haitao Wang, Maanav Mehrotra, Naman Chhikara, Di Sun. {xiaoyuch, wanght, maanav, namanchhikara, sdi1995} @vt.edu. Team 14: Facebook Data Breach April Fitzpatrick, Akshay Goel, Leah Hamilton, Ramya Nandigam, Esther Robb Final Presentation: 12/4/18 CS 4984/5984 Big Data Text Summarization - Taught by Dr. Edward Fox Document Summarization Abhirut Gupta Mandar Joshi Piyush Dungarwal Motivation The advent of WWW has created a large reservoir of data A short summary, which conveys the essence of the document, helps in finding relevant information quickly Diversity driven Attention Model for Query-based Abstractive Summarization Preksha Nema *,  Mitesh Khapra *,  Anirban Laha* # ,   Balaraman Ravindran * * Indian Institute of Technology Madras, India Ameet. Deshpande. March 24, 2020. TASK. Text Summarization is the reduction of data to a (minimal) subset which represents the original data. Two types of Summarization techniques. Extractive Summarization. (Combined Method). 1. Tatsuro. . Oya. Extractive Summarization + DA Recognition. . Locate . important sentences . in email and model . dialogue . acts . simultaneously. .. 2. Outline. Introduction. Reddit. Posts. with Multi-level Memory Networks. . [. NAACL . 2019]. Group Presentation. WANG, Yue. 04/15/2019. Outline. Background. Dataset. Method. Experiment. Conclusion. 2. /16. Background. Challenge:.