The event that the user is interested in is extracted from the unstructured information, and then displayed to the user in a structured way, that is event extraction. Event extraction has a wide range of applications in information collection, information retrieval, document synthesis, and information questioning and answering. From the overall perspective, event extraction algorithms can be divided into four categories: pattern matching algorithms, trigger lexical methods, ontology-based algorithms, and cutting-edge joint model methods. In the research process, different evaluation methods and datasets can be used according to the related needs, and different event representation methods are also related to event extraction research. Distinguished by task type, meta-event extraction and subject event extraction are the two basic tasks of event extraction. Among them, meta-event extraction has three methods based on pattern matching, machine learning and neural network respectively, while there are two ways to extract subjective events: based on the event framework and based on ontology respectively. Event extraction research has achieved excellent results in single languages such as Chinese and English, but cross-language event extraction still faces many problems. Finally, the related works of event extraction were summarized and the future research directions were prospected in order to provide guidelines for subsequent research.