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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 141150 of 359 papers

TitleStatusHype
Entity-Supported Summarization of Biomedical Abstracts0
Entity-Aware Abstractive Multi-Document Summarization0
End-to-end Argument Generation System in Debating0
Empirical analysis of exploiting review helpfulness for extractive summarization of online reviews0
ACM -- Attribute Conditioning for Abstractive Multi Document Summarization0
Efficient Online Summarization of Microblogging Streams0
A Supervised Aggregation Framework for Multi-Document Summarization0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization0
DualSum: a Topic-Model based approach for update summarization0
A Subjective Logic Framework for Multi-Document Summarization0
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