论文标题
概念漂移流的反应性软原型计算
Reactive Soft Prototype Computing for Concept Drift Streams
论文作者
论文摘要
自十年初以来，信息系统中代理之间的实时通信量迅速增加。这是因为这些系统的使用，e。 g。社交媒体在当今社会上已成为司空见惯。这需要分析算法实时学习和预测此信息流。这些系统的性质是非静态的，可以通过快速的趋势来解释。这创建了一个环境，在该环境中，算法必须识别变化并适应。最近的工作显示了该领域的重要研究，但在模型适应过程中主要缺乏稳定的性能。在这项工作中，提出了一种概念漂移检测策略，然后提出了基于原型的适应策略。通过对各种典型非静态数据的实验结果验证，我们的解决方案在变化时提供了稳定而快速的调整。
The amount of real-time communication between agents in an information system has increased rapidly since the beginning of the decade. This is because the use of these systems, e. g. social media, has become commonplace in today's society. This requires analytical algorithms to learn and predict this stream of information in real-time. The nature of these systems is non-static and can be explained, among other things, by the fast pace of trends. This creates an environment in which algorithms must recognize changes and adapt. Recent work shows vital research in the field, but mainly lack stable performance during model adaptation. In this work, a concept drift detection strategy followed by a prototype-based adaptation strategy is proposed. Validated through experimental results on a variety of typical non-static data, our solution provides stable and quick adjustments in times of change.
