[PDF][PDF] A survey of sequential pattern mining
P Fournier-Viger, JCW Lin… - Data Science and …, 2017 - philippe-fournier-viger.com
Discovering unexpected and useful patterns in databases is a fundamental data mining task.
In recent years, a trend in data mining has been to design algorithms for discovering …
In recent years, a trend in data mining has been to design algorithms for discovering …
A survey of utility-oriented pattern mining
W Gan, JCW Lin, P Fournier-Viger… - … on Knowledge and …, 2019 - ieeexplore.ieee.org
The main purpose of data mining and analytics is to find novel, potentially useful patterns
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …
that can be utilized in real-world applications to derive beneficial knowledge. For identifying …
Privacy-preserving multiobjective sanitization model in 6G IoT environments
JCW Lin, G Srivastava, Y Zhang… - IEEE internet of …, 2020 - ieeexplore.ieee.org
The next revolution of the smart industry relies on the emergence of the Industrial Internet of
Things (IoT) and 5G/6G technology. The properties of such sophisticated communication …
Things (IoT) and 5G/6G technology. The properties of such sophisticated communication …
[图书][B] Machine learning for data streams: with practical examples in MOA
A hands-on approach to tasks and techniques in data stream mining and real-time analytics,
with examples in MOA, a popular freely available open-source software framework. Today …
with examples in MOA, a popular freely available open-source software framework. Today …
A survey of evolutionary computation for association rule mining
Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …
in data mining. It has achieved great success in a plethora of applications such as market …
A survey of parallel sequential pattern mining
W Gan, JCW Lin, P Fournier-Viger, HC Chao… - ACM Transactions on …, 2019 - dl.acm.org
With the growing popularity of shared resources, large volumes of complex data of different
types are collected automatically. Traditional data mining algorithms generally have …
types are collected automatically. Traditional data mining algorithms generally have …
Using artificial intelligence techniques for COVID-19 genome analysis
The genome of the novel coronavirus (COVID-19) disease was first sequenced in January
2020, approximately a month after its emergence in Wuhan, capital of Hubei province …
2020, approximately a month after its emergence in Wuhan, capital of Hubei province …
Unsupervised learning for feature selection: A proposed solution for botnet detection in 5g networks
The world has seen exponential growth in deploying Internet of Things (IoT) devices. In
recent years, connected IoT devices have surpassed the number of connected non-IoT …
recent years, connected IoT devices have surpassed the number of connected non-IoT …
Fast utility mining on sequence data
W Gan, JCW Lin, J Zhang… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
High-utility sequential pattern (HUSP) mining is an emerging topic in the field of knowledge
discovery in databases. It consists of discovering subsequences that have a high utility …
discovery in databases. It consists of discovering subsequences that have a high utility …
A survey of high utility itemset mining
P Fournier-Viger, J Chun-Wei Lin, T Truong-Chi… - High-utility pattern …, 2019 - Springer
High utility pattern mining is an emerging data science task, which consists of discovering
patterns having a high importance in databases. The utility of a pattern can be measured in …
patterns having a high importance in databases. The utility of a pattern can be measured in …