The Role of Statistical and Semantic Features in Single-Document Extractive Summarization

Artificial Intelligence Research
doi 10.5430/air.v2n3p35
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Sciedu Press

Related search

Document Summarization Using TextRank and Semantic Network

International Journal of Intelligent Systems and Applications
ControlSignal ProcessingHuman-Computer InteractionOptimizationComputer NetworksSimulationCommunicationsComputer Science ApplicationsModelingArtificial Intelligence
2017English

Extractive Single Document Summarization Using Binary Differential Evolution: Optimization of Different Sentence Quality Measures

PLoS ONE
Multidisciplinary
2019English

Semantic Similarity Based Automatic Document Summarization Method

International Journal of Engineering and Advanced Technology
EngineeringComputer Science ApplicationsEnvironmental Engineering
2019English

RIN-Sum: A System for Query-Specific Multi-Document Extractive Summarization

International Journal of Advanced Computer Science and Applications
Computer Science
2017English

A Study of Semantic Augmentation of Word Embeddings for Extractive Summarization

2019English

Video Summarization Using Deep Semantic Features

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2017English

Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization

2019English

Polytope Model for Extractive Summarization

2012English

The Feasibility of Embedding Based Automatic Evaluation for Single Document Summarization

2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy