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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 91100 of 359 papers

TitleStatusHype
Error Analysis of using BART for Multi-Document Summarization: A Study for English and German LanguageCode0
Extractive Multi-document Summarization using K-means, Centroid-based Method, MMR, and Sentence PositionCode0
Disentangling Specificity for Abstractive Multi-document SummarizationCode0
AllSummarizer system at MultiLing 2015: Multilingual single and multi-document summarizationCode0
Bridging the gap between extractive and abstractive summaries: Creation and evaluation of coherent extracts from heterogeneous sourcesCode0
Scoring Sentence Singletons and Pairs for Abstractive SummarizationCode0
OpenAsp: A Benchmark for Multi-document Open Aspect-based SummarizationCode0
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous DataCode0
An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature ReviewCode0
ELSKE: Efficient Large-Scale Keyphrase ExtractionCode0
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