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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 221230 of 359 papers

TitleStatusHype
The UWB Summariser at Multiling-20130
Thread Specific Features are Helpful for Identifying Subjectivity Orientation of Online Forum Threads0
Topic-based Multi-document Summarization using Differential Evolution forCombinatorial Optimization of Sentences0
Topic-Centric Unsupervised Multi-Document Summarization of Scientific and News Articles0
Topic-Guided Abstractive Multi-Document Summarization0
Topic Models: Accounting Component Structure of Bigrams0
Towards Abstractive Multi-Document Summarization Using Submodular Function-Based Framework, Sentence Compression and Merging0
Towards a Neural Network Approach to Abstractive Multi-Document Summarization0
Towards Automatic Construction of News Overview Articles by News Synthesis0
Towards Coherent Multi-Document Summarization0
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