SOTAVerified

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 211220 of 359 papers

TitleStatusHype
Summarizing Complex Events: a Cross-Modal Solution of Storylines Extraction and Reconstruction0
Summarizing News Clusters on the Basis of Thematic Chains0
Summarizing World Speak : A Preliminary Graph Based Approach0
SumRecom: A Personalized Summarization Approach by Learning from Users' Feedback0
Supervised Learning of Automatic Pyramid for Optimization-Based Multi-Document Summarization0
System Combination for Multi-document Summarization0
Taking into account Inter-sentence Similarity for Update Summarization0
TGSum: Build Tweet Guided Multi-Document Summarization Dataset0
The Multilingual Paraphrase Database0
The SUMMA Platform: A Scalable Infrastructure for Multi-lingual Multi-media Monitoring0
Show:102550
← PrevPage 22 of 36Next →

No leaderboard results yet.