Amanote Research

Amanote Research

    RegisterSign In

Estimating Age on Twitter Using Self-Training Semi-Supervised SVM

Journal of Robotics, Networking and Artificial Life
doi 10.2991/jrnal.2016.3.1.6
Full Text
Open PDF
Abstract

Available in full text

Date

January 1, 2016

Authors
Tatsuyuki IjuSatoshi EndoKoji YamadaNaruaki TomaYuhei Akamine
Publisher

Atlantis Press


Related search

A Semi-Supervised Corpus Annotation for Saudi Sentiment Analysis Using Twitter

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2018English

Twitter Mining Using Semi-Supervised Classification for Relevance Filtering in Syndromic Surveillance

PLoS ONE
Multidisciplinary
2019English

Twitter Blogs Mining Using Supervised Algorithm

International Journal of Computer Applications
2015English

Semi-Supervised Training in Deep Learning Acoustic Model

2016English

Multi-Classifier Adaptive Training: Specialising an Activity Recognition Classifier Using Semi-Supervised Learning

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2012English

Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data

Remote Sensing
EarthPlanetary Sciences
2019English

Improving Semi-Supervised Classification Using Clustering

ICST Transactions on Scalable Information Systems
2018English

Semi-Supervised Clustering Using Heterogeneous Dissimilarities

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2010English

Semi-Supervised Object Recognition Using Structure Kernel

2012English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy