Event prediction is the ability of anticipating future events, i.e., future real-world occurrences, and aims to support the user in deciding on actions that change future events towards a desired state. An event prediction method learns the relation between features of past events and future events. It is applied to newly observed events to predict corresponding future events that are evaluated with respect to the user's desired future state. If the predicted future events do not comply with this state, actions are taken towards achieving desirable future states. Evidently, event prediction is valuable in many application domains such as business and natural disasters. The diversity of application domains results in a diverse range of methods that are scattered across various research areas which, in turn, use different terminology for event prediction methods. Consequently, sharing methods and knowledge for developing future event prediction methods is restricted. To facilitate knowledge sharing on account of a comprehensive classification, integration, and assessment of event prediction methods, we combine taxonomies and take a systems perspective to integrate event prediction methods into a single system, elicit requirements and assess existing work with respect to the requirements. Based on the assessment, we identify open challenges and discuss future research directions.

翻译：事件预测是预知未来事件（即未来真实世界发生的事件）的能力，旨在帮助用户决策，以将未来事件引导至期望状态。事件预测方法通过学习过去事件特征与未来事件之间的关系，将新观察到的事件应用于预测对应的未来事件，并根据用户期望的未来状态进行评估。若预测结果不符合期望状态，则采取行动以实现期望的未来状态。显然，事件预测在商业和自然灾害等众多应用领域具有重要价值。应用领域的多样性导致预测方法分散于不同研究领域，且各领域对事件预测方法的术语使用存在差异，从而限制了方法交流与知识共享。为促进基于全面分类、整合与评估的事件预测方法知识共享，我们综合现有分类体系，从系统视角将各类事件预测方法整合为统一系统，明确相关需求，并依据需求评估现有工作。基于评估结果，我们指出当前面临的挑战，并探讨未来研究方向。