Interactive Abstractive Summarization for Event News Tweets
نویسندگان
چکیده
We present a novel interactive summarization system that is based on abstractive summarization, derived from a recent consolidated knowledge representation for multiple texts. We incorporate a couple of interaction mechanisms, providing a bullet-style summary while allowing to attain the most important information first and interactively drill down to more specific details. A usability study of our implementation, for event news tweets, suggests the utility of our approach for text exploration.
منابع مشابه
Abstractive News Summarization based on Event Semantic Link Network
This paper studies the abstractive multi-document summarization for event-oriented news texts through event information extraction and abstract representation. Fine-grained event mentions and semantic relations between them are extracted to build a unified and connected event semantic link network, an abstract representation of source texts. A network reduction algorithm is proposed to summariz...
متن کاملTGSum: Build Tweet Guided Multi-Document Summarization Dataset
The development of summarization research has been significantly hampered by the costly acquisition of reference summaries. This paper proposes an effective way to automatically collect large scales of news-related multi-document summaries with reference to social media’s reactions. We utilize two types of social labels in tweets, i.e., hashtags and hyper-links. Hashtags are used to cluster doc...
متن کاملTowards Improving Abstractive Summarization via Entailment Generation
Abstractive summarization, the task of rewriting and compressing a document into a short summary, has achieved considerable success with neural sequence-tosequence models. However, these models can still benefit from stronger natural language inference skills, since a correct summary is logically entailed by the input document, i.e., it should not contain any contradictory or unrelated informat...
متن کاملQuery-Based Abstractive Summarization Using Neural Networks
In this paper, we present a model for generating summaries of text documents with respect to a query. This is known as querybased summarization. We adapt an existing dataset of news article summaries for the task and train a pointer-generator model using this dataset. The generated summaries are evaluated by measuring similarity to reference summaries. Our results show that a neural network sum...
متن کاملAbstractive Summarization for Amazon Reviews
This paper focuses on feed-forward neural network with attention-based encoder to solve the challenge of abstractive summarization. We also briefly explored the potential of attentive recurrent neural network and recurrent neural network encoder-decoder. Those models were originally proposed to solve similar tasks, such as news articles summarization and machine translation; we modify and exten...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017