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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 301310 of 359 papers

TitleStatusHype
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous DataCode0
Extractive Multi-document Summarization using K-means, Centroid-based Method, MMR, and Sentence PositionCode0
Modeling Endorsement for Multi-Document Abstractive SummarizationCode0
AllSummarizer system at MultiLing 2015: Multilingual single and multi-document summarizationCode0
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource LanguagesCode0
Revisiting Sentence Union Generation as a Testbed for Text ConsolidationCode0
SumREN: Summarizing Reported Speech about Events in NewsCode0
Fair Summarization: Bridging Quality and Diversity in Extractive SummariesCode0
Compressed Heterogeneous Graph for Abstractive Multi-Document SummarizationCode0
Fast Concept Mention Grouping for Concept Map-based Multi-Document SummarizationCode0
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