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 291300 of 359 papers

TitleStatusHype
Exploiting Timelines to Enhance Multi-document Summarization0
A Hybrid Approach to Multi-document Summarization of Opinions in Reviews0
Detection of Topic and its Extrinsic Evaluation Through Multi-Document Summarization0
Hierarchical Summarization: Scaling Up Multi-Document Summarization0
Multi-document summarization using distortion-rate ratio0
Query-Chain Focused Summarization0
Multi-layered graph-based multi-document summarization model0
Summarizing News Clusters on the Basis of Thematic Chains0
LQVSumm: A Corpus of Linguistic Quality Violations in Multi-Document Summarization0
Extracting News Web Page Creation Time with DCTFinder0
Show:102550
← PrevPage 30 of 36Next →

No leaderboard results yet.