Nowadays, with the advance of technology, many applications generate huge amounts of
data streams at very high speed. Examples include network traffic, web click streams, video …

This book is concerned with the concept, the theories, and the implementations of text
mining. In Part I, we provide the fundamental knowledge about the text mining tasks, such as …

This paper aims to enhance event detection methods in a micro-blogging platform, namely
Twitter. The enhancement technique we propose is based on lexico-semantic expansion of …

Webpage recommendations for hot Web events can assist people to easily follow the
evolution of these Web events. At the same time, there are different levels of semantic …

Automatically analysing the emotion in texts is in increasing interest in today's research
fields. The aim is to develop a machine that can detect type of user's emotion from his/her …

A wide number of reports and news on crimes, increasingly conducted almost every day,
have resulted in making detection of such crimes more difficult if not complex. Therefore, the …

We study on-the-fly classification of evolving text streams in which the relation between the
input data and target labels changes over time—ie,“concept drift.” These variations decrease …

In multiword expression (MWE) recognition, there exist many studies where different
learning methods are employed to decide whether given word combination is a multiword …

The objective of this paper is to propose a hierarchical topic evolution model (HTEM) that
can organize time‐varying topics in a hierarchy and discover their evolutions with multiple …

Abstract First Story Detection (FSD) aims to identify the first story for an emerging event
previously unreported, which is essential to practical applications in news analysis …