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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 251260 of 359 papers

TitleStatusHype
Multi2: Multi-Agent Test-Time Scalable Framework for Multi-Document Processing0
Multi-document abstractive summarization using ILP based multi-sentence compression0
Multi-document multilingual summarization corpus preparation, Part 1: Arabic, English, Greek, Chinese, Romanian0
Multi-document multilingual summarization corpus preparation, Part 2: Czech, Hebrew and Spanish0
Multi-document multilingual summarization and evaluation tracks in ACL 2013 MultiLing Workshop0
Multi-Document Summarization withDeterminantal Point Process Attention0
Multi-document Summarization: A Comparative Evaluation0
Multi-Document Summarization of Persian Text using Paragraph Vectors0
Multi-Document Summarization using Distributed Bag-of-Words Model0
Multi-Document Summarization using Automatic Key-Phrase Extraction0
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