Query-Based Abstractive Summarization Using Neural Networks
Computation and Language
2017-12-19 v1
Abstract
In this paper, we present a model for generating summaries of text documents with respect to a query. This is known as query-based 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 summarization model, similar to existing neural network models for abstractive summarization, can be constructed to make use of queries to produce targeted summaries.
Cite
@article{arxiv.1712.06100,
title = {Query-Based Abstractive Summarization Using Neural Networks},
author = {Johan Hasselqvist and Niklas Helmertz and Mikael Kågebäck},
journal= {arXiv preprint arXiv:1712.06100},
year = {2017}
}