Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

Data preprocessing and reduction have become essential techniques in current knowledge
discovery scenarios, dominated by increasingly large datasets. These methods aim at …

大数据为智能电网的发展注入新的活力, 掌握电力大数据的关键技术对电力行业的可持续发展和
坚强智能电网的建立具有重要意义. 在分析大数据, 云计算, 智能电网三者关系的基础上 …

摘要随着产业界数据量的爆炸式增长, 大数据概念受到越来越多的关注. 由于大数据的海量,
复杂多样, 变化快的特性, 对于大数据环境下的应用问题, 传统的在小数据上的机器学习算法很多 …

Malicious URL, aka malicious website, is a common and serious threat to cybersecurity.
Malicious URLs host unsolicited content (spam, phishing, drive-by exploits, etc.) and lure …

In an era of growing data complexity and volume and the advent of big data, feature
selection has a key role to play in helping reduce high-dimensionality in machine learning …

as an attempt to understand Modern Learning Environment (MLE) to support learning in big
data era, its exploration where the students are engaged to access online resources using …

With the proliferation of online services and mobile technologies, the world has stepped into
a multimedia big data era. A vast amount of research work has been done in the multimedia …

Research on big data analytics is entering in the new phase called fast data where multiple
gigabytes of data arrive in the big data systems every second. Modern big data systems …

Feature selection is an important technique for data mining. Despite its importance, most
studies of feature selection are restricted to batch learning. Unlike traditional batch learning …