IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Special Section on Information and Communication Systems for Safe and Secure Life
Identifying Important Tweets by Considering the Potentiality of Neurons
Ryozo KITAJIMARyotaro KAMIMURAOsamu UCHIDAFujio TORIUMI
Author information
JOURNALS RESTRICTED ACCESS

2016 Volume E99.A Issue 8 Pages 1555-1559

Details
Abstract

The purpose of this paper is to show that a new type of information-theoretic learning method called “potential learning” can be used to detect and extract important tweets among a great number of redundant ones. In the experiment, we used a dataset of 10,000 tweets, among which there existed only a few important ones. The experimental results showed that the new method improved overall classification accuracy by correctly identifying the important tweets.

Information related to the author
© 2016 The Institute of Electronics, Information and Communication Engineers
Previous article Next article
feedback
Top