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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
Automatic Generation of Related Work Sections in Scientific Papers: An Optimization Approach0
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
Exploring Text Links for Coherent Multi-Document Summarization0
Extractive Multi-Document Summarization with Integer Linear Programming and Support Vector Regression0
Exploiting Timelines to Enhance Multi-document Summarization0
Automatically Summarizing Evidence from Clinical Trials: A Prototype Highlighting Current Challenges0
Analyzing Stemming Approaches for Turkish Multi-Document Summarization0
Exploiting Timegraphs in Temporal Relation Classification0
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