Over the past few years, neural networks have re-emerged as powerful machine-learning
models, yielding state-of-the-art results in fields such as image recognition and speech …

Selection of text feature item is a basic and important matter for text mining and information
retrieval. Traditional methods of feature extraction require handcrafted features. To hand …

The problem of event extraction requires detecting the event trigger and extracting its
corresponding arguments. Existing work in event argument extraction typically relies heavily …

Event extraction requires high-quality expert human annotations, which are usually
expensive. Therefore, learning a data-efficient event extraction model that can be trained …

Traditional approaches to the task of ACE event extraction usually depend on manually
annotated data, which is often laborious to create and limited in size. Therefore, in addition …

Neural networks are a family of powerful machine learning models. This book focuses on the
application of neural network models to natural language data. The first half of the book …

The current neural network models for event detection have only considered the sequential
representation of sentences. Syntactic representations have not been explored in this area …

The growth of online services has been accompanied by increased growth in cyber-attacks.
One of the most common effective attacks is phishing, in which attempts are made to steal …

Event extraction is a particularly challenging problem in information extraction. The stateof-
the-art models for this problem have either applied convolutional neural networks in a …

Numerous important events happen everyday and everywhere but are reported in different
media sources with different narrative styles. How to detect whether real-world events have …