Concept Drift Adaptation in Text Stream Mining Settings: A Comprehensive Review
Due to the advent and increase in the popularity of the Internet, people have been producing
and disseminating textual data in several ways, such as reviews, social media posts, and …
and disseminating textual data in several ways, such as reviews, social media posts, and …
[HTML][HTML] Introduction to focus issue: Recurrence quantification analysis for understanding complex systems
In 1987, recurrence plots were first introduced by Eckmann, Oliffson-Kamphorst, and Ruelle
as a simple graphical tool to visualize basic dynamical characteristics of time series. 1 This …
as a simple graphical tool to visualize basic dynamical characteristics of time series. 1 This …
Concept drift adaptation in text stream mining settings: a systematic review
The society produces textual data online in several ways, eg, via reviews and social media
posts. Therefore, numerous researchers have been working on discovering patterns in …
posts. Therefore, numerous researchers have been working on discovering patterns in …
Dynamically adaptive and diverse dual ensemble learning approach for handling concept drift in data streams
Abstract Concept drift refers to the change in data distributions and evolving relationships
between input and output variables with the passage of time. To analyze such variations in …
between input and output variables with the passage of time. To analyze such variations in …
Event-driven Sentiment Drift Analysis in Text Streams: An Application in a Soccer Match
CM Garcia, A de Souza Britto… - … Conference on Machine …, 2023 - ieeexplore.ieee.org
Social media has been a data source for various applications, given its characteristic of
working as a social sensor. Many applications in several areas, such as brand reputation …
working as a social sensor. Many applications in several areas, such as brand reputation …
Concept drift detection for social media: A survey
The research over information retrieval from social media data has progressed for streaming
data since the last decade. Recently, academic researchers have witnessed users' changing …
data since the last decade. Recently, academic researchers have witnessed users' changing …
Quantifying temporal novelty in social networks using time-varying graphs and concept drift detection
VMG dos Santos, RF de Mello, T Nogueira… - Intelligent Systems: 9th …, 2020 - Springer
This paper presents a new approach to quantify temporal novelties in Social Networks and,
as a consequence, to identify changing points driven by the occurrence of new real-world …
as a consequence, to identify changing points driven by the occurrence of new real-world …
Dynamically updated diversified ensemble-based approach for handling concept drift
Abstract Concept drift is the phenomenon where underlying data distribution changes over
time unexpectedly. Examining such drifts and getting insight into the executing processes at …
time unexpectedly. Examining such drifts and getting insight into the executing processes at …
[PDF][PDF] Security Enhancing Technologies for Cloud-of-Clouds
JMMS de Resende - 2021 - repositorio-aberto.up.pt
In recent years, cybersecurity experts have been developing mechanisms to protect users
and devices, but there is a constant” arms race” between attackers and defenders. With …
and devices, but there is a constant” arms race” between attackers and defenders. With …
Impact of Randomization on Ensembles for Streams with Concept Drift
In the present era many real world applications are built from streaming data. The
distribution of underlying data in such streams tend to change with course of time called as …
distribution of underlying data in such streams tend to change with course of time called as …