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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 261270 of 359 papers

TitleStatusHype
A Discursive Grid Approach to Model Local Coherence in Multi-document Summaries0
Affinity-Preserving Random Walk for Multi-Document Summarization0
AgreeSum: Agreement-Oriented Multi-Document Summarization0
A Hybrid Approach to Multi-document Summarization of Opinions in Reviews0
A Method of Accounting Bigrams in Topic Models0
A Multi-Document Coverage Reward for RELAXed Multi-Document Summarization0
A Multi-level Annotated Corpus of Scientific Papers for Scientific Document Summarization and Cross-document Relation Discovery0
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization0
Analyzing Stemming Approaches for Turkish Multi-Document Summarization0
An Assessment of the Accuracy of Automatic Evaluation in Summarization0
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