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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

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Showing 326–350 of 359 papers

TitleStatusHype
Multi-document multilingual summarization and evaluation tracks in ACL 2013 MultiLing Workshop—0
Using a Keyness Metric for Single and Multi Document Summarisation—0
Multi-document multilingual summarization corpus preparation, Part 2: Czech, Hebrew and Spanish—0
Fast and Robust Compressive Summarization with Dual Decomposition and Multi-Task Learning—0
CIST System Report for ACL MultiLing 2013 -- Track 1: Multilingual Multi-document Summarization—0
Multi-document multilingual summarization corpus preparation, Part 1: Arabic, English, Greek, Chinese, Romanian—0
Towards Robust Abstractive Multi-Document Summarization: A Caseframe Analysis of Centrality and Domain—0
Proceedings of the MultiLing 2013 Workshop on Multilingual Multi-document Summarization—0
Probabilistic Domain Modelling With Contextualized Distributional Semantic Vectors—0
A Preliminary Study of Tweet Summarization using Information Extraction—0
Drug Extraction from the Web: Summarizing Drug Experiences with Multi-Dimensional Topic Models—0
Towards Coherent Multi-Document Summarization—0
Using POMDPs for Topic-Focused Multi-Document Summarization (L'utilisation des POMDP pour les r\'esum\'es multi-documents orient\'es par une th\'ematique) [in French]—0
A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization—0
Query-focused Multi-document Summarization: Combining a Novel Topic Model with Graph-based Semi-supervised Learning—0
Extractive Multi-Document Summarization with Integer Linear Programming and Support Vector Regression—0
On the Effectiveness of using Sentence Compression Models for Query-Focused Multi-Document Summarization—0
Update Summarization Based on Co-Ranking with Constraints—0
A Supervised Aggregation Framework for Multi-Document Summarization—0
A Subjective Logic Framework for Multi-Document Summarization—0
RelationListwise for Query-Focused Multi-Document Summarization—0
Exploiting Category-Specific Information for Multi-Document Summarization—0
Thread Specific Features are Helpful for Identifying Subjectivity Orientation of Online Forum Threads—0
SentTopic-MultiRank: a Novel Ranking Model for Multi-Document Summarization—0
Framework of Automatic Text Summarization Using Reinforcement Learning—0
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