A survey on data preprocessing for data stream mining: Current status and future directions
Data preprocessing and reduction have become essential techniques in current knowledge
discovery scenarios, dominated by increasingly large datasets. These methods aim at …
discovery scenarios, dominated by increasingly large datasets. These methods aim at …
Data stream mining in ubiquitous environments: state‐of‐the‐art and current directions
In this article, we review the state‐of‐the‐art techniques in mining data streams for mobile
and ubiquitous environments. We start the review with a concise background of data stream …
and ubiquitous environments. We start the review with a concise background of data stream …
Edge computing framework for enabling situation awareness in IoT based smart city
SKA Hossain, MA Rahman, MA Hossain - Journal of Parallel and …, 2018 - Elsevier
Abstract The Internet of Things (IoT) offers a lot of benefits for building smart cities. Such
cities will be able to utilize a huge number of heterogeneous IoT devices that can generate a …
cities will be able to utilize a huge number of heterogeneous IoT devices that can generate a …
Finding the tipping point: When heterogeneous evaluations in social media converge and influence organizational legitimacy
Can citizens impact the broader discourse about an organization and its legitimacy? While
social media have empowered citizens to publicly question firms through large volumes of …
social media have empowered citizens to publicly question firms through large volumes of …
[PDF][PDF] Dynamic feature space and incremental feature selection for the classification of textual data streams
I Katakis, G Tsoumakas… - … Discovery from Data …, 2006 - intelligence.csd.auth.gr
Real world text classification applications are of special interest for the machine learning
and data mining community, mainly because they introduce and combine a number of …
and data mining community, mainly because they introduce and combine a number of …
Dynamic feature selection for clustering high dimensional data streams
Change in a data stream can occur at the concept level and at the feature level. Change at
the feature level can occur if new, additional features appear in the stream or if the …
the feature level can occur if new, additional features appear in the stream or if the …
Mining recurring concepts in a dynamic feature space
Most data stream classification techniques assume that the underlying feature space is
static. However, in real-world applications the set of features and their relevance to the target …
static. However, in real-world applications the set of features and their relevance to the target …
Online hierarchical streaming feature selection based on adaptive neighborhood rough set
T Shu, Y Lin, L Guo - Applied Soft Computing, 2024 - Elsevier
In the era of open machine learning, a kind of data is accompanied by a hierarchical
structure between classes in the label space and the increasing number of features …
structure between classes in the label space and the increasing number of features …
Online indexing and clustering of social media data for emergency management
D Pohl, A Bouchachia, H Hellwagner - Neurocomputing, 2016 - Elsevier
Social media becomes a vital part in our daily communication practice, creating a huge
amount of data and covering different real-world situations. Currently, there is a tendency in …
amount of data and covering different real-world situations. Currently, there is a tendency in …
On feature extraction for spam e-mail detection
Electronic mail is an important communication method for most computer users. Spam e-
mails however consume bandwidth resource, fill-up server storage and are also a waste of …
mails however consume bandwidth resource, fill-up server storage and are also a waste of …