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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 271280 of 359 papers

TitleStatusHype
Multilingual Single-Document Summarization with MUSE0
Multilingual Summarization: Dimensionality Reduction and a Step Towards Optimal Term Coverage0
Multilingual summarization system based on analyzing the discourse structure at MultiLing 20130
Multiple Aspect Summarization Using Integer Linear Programming0
Multi-Topic Multi-Document Summarizer0
Neighborhood Rough Set based Multi-document Summarization0
Neural Abstractive Multi-Document Summarization: Hierarchical or Flat Structure?0
Neural Abstractive Summarization with Structural Attention0
Neural Sentence Ordering0
NewsQs: Multi-Source Question Generation for the Inquiring Mind0
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