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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 291300 of 359 papers

TitleStatusHype
Corpora Evaluation and System Bias Detection in Multi-document SummarizationCode0
A Multi-Document Coverage Reward for RELAXed Multi-Document SummarizationCode0
Non-Parametric Memory Guidance for Multi-Document SummarizationCode0
MDSWriter: Annotation Tool for Creating High-Quality Multi-Document Summarization CorporaCode0
Read what you need: Controllable Aspect-based Opinion Summarization of Tourist ReviewsCode0
Nutri-bullets: Summarizing Health Studies by Composing SegmentsCode0
Extending Multi-Document Summarization Evaluation to the Interactive SettingCode0
Extending Multi-Text Sentence Fusion Resources via Pyramid AnnotationsCode0
OARelatedWork: A Large-Scale Dataset of Related Work Sections with Full-texts from Open Access SourcesCode0
MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News SummarizationCode0
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