Neural Network-Based Abstract Generation for Opinions and Arguments
23577Authors
nan
Abstract
Generation for Opinions and Arguments Lu Wang College of Computer and Information Science Northeastern University Boston, MA 02115 luwang@ccs.neu.edu Wang Ling Google DeepMind London, N1 0AE lingwang@google.com Abstract We study the problem of generating abstrac- tive summaries for opinionated text. We pro- pose an attention-based neural network model that is able to absorb information from multi- ple text units to construct informative, concise, and fluent summaries. An importance-based sampling method is designed to allow the en- coder to integrate information from an impor- tant subset of input. Automatic evaluation in- dicates that our system outperforms state-of- the-art abstractive and extractive summariza- tion systems on two newly collected datasets of movie reviews and arguments. Our system summaries are also rated as more informative and grammatical in human evaluation. 1
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Proceedings of NAACL-HLT 2016, pages 47–57, San Diego, California, June 12-17, 2016. c⃝2016 Association for Computational Linguistics Neural Network-Based Abstract Generation for Opinions and Arguments Lu Wang College of Computer and Information Science Northeastern University Boston, MA 02115 luwang@ccs.neu.edu Wang Ling Google DeepMind London, N1 0AE lingwang@google.com Abstract We study the problem of generating abstrac- tive summaries for opinionated text. We pro- pose an attention-based neural network model that is able to absorb information from multi- ple text units to construct informative, concise, and fluent summaries. An importance-based sampling method is designed to allow the en- coder to integrate information from an impor- tant subset of input. Automatic evaluation in- dicates that our system outperforms state-of- the-art abstractive and extractive summariza- tion systems on two newly collected datasets of movie reviews and arguments. Our system summaries are also rated as more informative and grammatical in human evaluation. 1 Introduction Collecting opinions from others is an integral part of our daily activities. Discovering what other peo- ple think can help us navigate through different as- pects of life, ranging from making decisions on reg- ular tasks to judging fundamental societal issues and forming personal ideology. To efficiently absorb the massive amount of opinionated information, there is a pressing need for automated systems that can gen- erate concise and fluent opinion summary about an entity or a topic. In spite of substantial researches in opinion summarization, the most prominent ap- proaches mainly rely on extractive summarization methods, where phrases or sentences from the origi- nal documents are selected for inclusion in the sum- mary (Hu and Liu, 2004; Lerman et al., 2009). One of the problems that extractive methods suffer from Movie: The Martian Reviews: - One the smartest, sweetest, and most satisfyingly suspenseful sci-fi films in years. - ...an intimate sci-fi epic that is smart, spectacular and stirring. - The Martian is a thrilling, human and moving sci-fi picture that is easily the most emotionally engaging film Ridley Scott has made... - It’s pretty sunny and often funny, a space oddity for a director not known for pictures with a sense of humor. - The Martian highlights the book’s best qualities, tones down its worst, and adds its own style... Opinion Consensus (Summary): Smart, thrilling, and sur- prisingly funny, The Martian offers a faithful adaptation of the bestselling book that brings out the best in leading man Matt Damon and director Ridley Scott. Topic: This House supports the death penalty. Arguments: - The state has a responsibility to protect the lives of innocent citizens, and enacting the death penalty may save lives by re- ducing the rate of violent crime. - While the prospect of life in prison may be frightening, surely death is a more daunting prospect. - A 1985 study by Stephen K. Layson at the University of North Carolina showed that a single execution deters 18 murders. - Reducing the wait time on death row prior to execution can dramatically increase its deterrent effect in the United States. …
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Generation for Opinions and Arguments Lu Wang College of Computer and Information Science Northeastern University Boston, MA 02115 Wang Ling Google DeepMind London, N1 0AE Abstract We study the problem of generating abstractive summaries for opinionated text. We propose an attention-based neural network model that is able to absorb information from multiple text units to construct informative, concise, and fluent summaries. An importance-based sampling method is designed to allow the encoder to integrate information from an important subset of input. Automatic evaluation indicates that our system outperforms state-ofthe-art abstractive and extractive summarization systems on two newly collected datasets of movie reviews and arguments. Our system summaries are also rated as more informative and grammatical in human evaluation. 1
Publication Details
- Paper ID:
- 23577
- Year:
- 2016
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan