Node classification is an important problem in relational machine learning. However, in
scenarios where graph edges represent interactions among the entities (eg, over time), the …

As an effort to detect the mood of a blog, regardless of the length and writing style, we
propose a hybrid approach to detecting blog text’s mood, which incorporates commonsense …

With advances in artificial intelligence (AI)-based algorithms, gesture recognition accuracy
from sEMG signals has continued to increase. Spatiotemporal multichannel-sEMG signals …

The counterfeiting of products is a serious concern for any nation with the increasing activity
of counterfeit markets. Anticounterfeiting tags demand low‐cost, unclonable, facile, and …

A lot of knowledge about procedures and how-tos are described in text. Recently, extracting
semantic relations from the procedural text has been actively explored. Prior work mostly …

Learning with graph-structured data, such as social, biological, and financial networks, requires
effective low-dimensional representations to handle their large and complex interactions…

This study investigated the underlying mechanisms of online social media group behaviors
in an emergency. The proposed framework was designed to analyze group behaviors/…

Numerical reasoning is an essential task for supporting machine learning applications, such
as recommendation and information retrieval. The reasoning task aims to compare two …

Abstract Machine learning (ML) models have been quite successful in predicting outcomes
in many applications. However, in some cases, domain experts might have a judgment about …

Node representation learning in a network is an important machine learning technique for
encoding relational information in a continuous vector space while preserving the inherent …