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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 161170 of 359 papers

TitleStatusHype
Deep Attentive Sentence Ordering Network0
A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization0
Deconstructing Human Literature Reviews -- A Framework for Multi-Document Summarization0
Data-driven Paraphrasing and Stylistic Harmonization0
A Repository of State of the Art and Competitive Baseline Summaries for Generic News Summarization0
Abstract Meaning Representation for Multi-Document Summarization0
Creation and use of Language Resources in a Question-Answering eHealth System0
A Repository of Corpora for Summarization0
基于实体信息增强及多粒度融合的多文档摘要(Multi-Document Summarization Based on Entity Information Enhancement and Multi-Granularity Fusion)0
Interactive Abstractive Summarization for Event News Tweets0
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