Multi-document summarization via deep learning techniques: A survey
Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …
generates an informative and concise summary from a cluster of topic-related documents …
A review on human-computer interaction and intelligent robots
F Ren, Y Bao - International Journal of Information Technology & …, 2020 - World Scientific
In the field of artificial intelligence, human–computer interaction (HCI) technology and its
related intelligent robot technologies are essential and interesting contents of research …
related intelligent robot technologies are essential and interesting contents of research …
Neural document summarization by jointly learning to score and select sentences
Sentence scoring and sentence selection are two main steps in extractive document
summarization systems. However, previous works treat them as two separated subtasks. In …
summarization systems. However, previous works treat them as two separated subtasks. In …
Faithful to the original: Fact aware neural abstractive summarization
Unlike extractive summarization, abstractive summarization has to fuse different parts of the
source text, which inclines to create fake facts. Our preliminary study reveals nearly 30% of …
source text, which inclines to create fake facts. Our preliminary study reveals nearly 30% of …
Recent automatic text summarization techniques: a survey
M Gambhir, V Gupta - Artificial Intelligence Review, 2017 - Springer
As information is available in abundance for every topic on internet, condensing the
important information in the form of summary would benefit a number of users. Hence, there …
important information in the form of summary would benefit a number of users. Hence, there …
Abstractive document summarization with a graph-based attentional neural model
Abstractive summarization is the ultimate goal of document summarization research, but
previously it is less investigated due to the immaturity of text generation techniques …
previously it is less investigated due to the immaturity of text generation techniques …
Graph-based neural multi-document summarization
We propose a neural multi-document summarization (MDS) system that incorporates
sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation …
sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation …
Summarizing opinions: Aspect extraction meets sentiment prediction and they are both weakly supervised
S Angelidis, M Lapata - arXiv preprint arXiv:1808.08858, 2018 - arxiv.org
We present a neural framework for opinion summarization from online product reviews
which is knowledge-lean and only requires light supervision (eg, in the form of product …
which is knowledge-lean and only requires light supervision (eg, in the form of product …
Extractive opinion summarization in quantized transformer spaces
Abstract We present the Quantized Transformer (QT), an unsupervised system for extractive
opinion summarization. QT is inspired by Vector-Quantized Variational Autoencoders, which …
opinion summarization. QT is inspired by Vector-Quantized Variational Autoencoders, which …
Scisummnet: A large annotated corpus and content-impact models for scientific paper summarization with citation networks
Scientific article summarization is challenging: large, annotated corpora are not available,
and the summary should ideally include the article's impacts on research community. This …
and the summary should ideally include the article's impacts on research community. This …