The present study reviews the publications that examine the application of machine learning
(ML) approaches in occupational accident analysis. The review process includes four …

With more and more data generated, it has become a big challenge for traditional
architectures and infrastructures to process large amounts of data within an acceptable time …

Association rule mining (ARM) is a commonly encountred data mining method. There are
many approaches to mining frequent rules and patterns from a database and one among …

In recent years, fashion e-commerce has become more and more popular. Since there are
so many fashion products provided by e-commerce retailers, it is necessary to provide …

Association rule mining is intended for searching for the relationships between attributes in
transaction databases. The whole process of rule discovery is very complex, and involves …

The machine learning algorithms exploit a given dataset in order to build an efficient
predictive or descriptive model. Multi-objective evolutionary optimization assists machine …

Discriminative sequential patterns are sub-sequences whose occurrences exhibit significant
differences across sequential data sets with different class labels. The discovery of such …

Abstract The Jing-Jin-Ji region of Northern China has experienced serious extreme PM
concentrations, which could exert considerable negative impacts on human health …

Data mining is essentially applied to discover new knowledge from a database through an
iterative process. The mining process may be time consuming for massive datasets. A widely …

Although the research into causal effects has always been the core part of safety science,
the formal mathematical method to infer causal effects is quite new. With the rapid …