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Multi-Document Summarization

Multi-Document Summarization is a process of representing a set of documents with a short piece of text by capturing the relevant information and filtering out the redundant information. Two prominent approaches to Multi-Document Summarization are extractive and abstractive summarization. Extractive summarization systems aim to extract salient snippets, sentences or passages from documents, while abstractive summarization systems aim to concisely paraphrase the content of the documents.

Source: Multi-Document Summarization using Distributed Bag-of-Words Model

Papers

Showing 121130 of 359 papers

TitleStatusHype
BASS: Boosting Abstractive Summarization with Unified Semantic Graph0
Extracting News Web Page Creation Time with DCTFinder0
Extractive Multi-document Summarization Using Multilayer Networks0
Extractive Multi Document Summarization using Dynamical Measurements of Complex Networks0
BERT-VBD: Vietnamese Multi-Document Summarization Framework0
Extractive Multi-Document Summarization with Integer Linear Programming and Support Vector Regression0
CIST System Report for ACL MultiLing 2013 -- Track 1: Multilingual Multi-document Summarization0
Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization0
CIST System for CL-SciSumm 2016 Shared Task0
Ant Colony System for Multi-Document Summarization0
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