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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 176–200 of 359 papers

TitleStatusHype
Using a Keyness Metric for Single and Multi Document Summarisation—0
Using External Resources and Joint Learning for Bigram Weighting in ILP-Based 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
Using Shallow Semantic Parsing and Relation Extraction for Finding Contradiction in Text—0
Using Statistical and Semantic Models for Multi-Document Summarization—0
Utilizing Automatic Predicate-Argument Analysis for Concept Map Mining—0
Vector Space Models for Scientific Document Summarization—0
What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization—0
Evaluating Pre-Trained Language Models on Multi-Document Summarization for Literature Reviews—0
EventSum: A Large-Scale Event-Centric Summarization Dataset for Chinese Multi-News Documents—0
Evolutionary Hierarchical Dirichlet Process for Timeline Summarization—0
ExB Text Summarizer—0
Exploiting Category-Specific Information for Multi-Document Summarization—0
Exploiting Timegraphs in Temporal Relation Classification—0
Exploiting Timelines to Enhance Multi-document Summarization—0
Exploring Text Links for Coherent Multi-Document Summarization—0
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval—0
Exploring the limits of a base BART for multi-document summarization in the medical domain—0
Extending a Single-Document Summarizer to Multi-Document: a Hierarchical Approach—0
Extracting News Web Page Creation Time with DCTFinder—0
Extractive Multi-document Summarization Using Multilayer Networks—0
Extractive Multi Document Summarization using Dynamical Measurements of Complex Networks—0
Extractive Multi-Document Summarization with Integer Linear Programming and Support Vector Regression—0
Extractive Summarization by Aggregating Multiple Similarities—0
Extractive Summarization: Limits, Compression, Generalized Model and Heuristics—0
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