Recently, incremental and on-line learning gained more attention especially in the context of
big data and learning from data streams, conflicting with the traditional assumption of …

Twitter is among the fastest‐growing microblogging and online social networking services.
Messages posted on Twitter (tweets) have been reporting everything from daily life stories to …

Social media platforms, or social networks, have allowed millions of users to post online
content about topics related to our daily lives. Traffic is one of the many topics for which …

Modern networks generate a massive amount of traffic data streams. Analyzing this data is
essential for various purposes, such as network resources management and cyber-security …

Data caps and service degradation are techniques used to control subscribers' data
consumption. These techniques have emerged mainly due to the growing demands placed …

Data analytics techniques have been used for numerous manufacturing applications in
various areas. A common assumption of data analytics models is that the environment that …

Incremental learning has become a new research hotspot in the field of machine learning.
Compared with traditional machine learning, incremental learning can continuously learn …

The intrusion or attack in the computer network is one of the most important issues in Cloud
environment. Due to enormous network traffic, dynamic and incremental learning is …

In this paper, we propose a novel life-long learning framework, which constantly evolves
with changing data distribution, learning new knowledge while retaining some old …

The most effective well-known methods in the context of static machine learning offer no
alternative to evolution and dynamic adaptation to integrate new data or to restructure …