A fundamental problem in text data mining is to extract meaningful structure from document
streams that arrive continuously over time. E-mail and news articles are two natural …

As datasets grow and analytic algorithms become more complex, the typical workflow of
analysts launching an analytic, waiting for it to complete, inspecting the results, and then re …

Text classification is a major data mining task. An advanced text classification technique is
known as partially supervised text classification, which can build a text classifier using a …

Data mining is the task of discovering interesting patterns in large amounts of data where the
data can be stored in a database, data warehouses, or other information repositories. It is a …

Temporal event sequence data is increasingly commonplace, with applications ranging from
electronic medical records to financial transactions to social media activity. Previously …

A number of recent computing applications involve information arriving continuously over
time in the form of a data stream, and this has led to new ways of thinking about traditional …

As high volumes of a wide variety of valuable data of different veracities can be easily
generated or collected at a high velocity nowadays, big data visualisation and visual …

The aim of this work is to survey and reflect on the various ways visualization and data
mining can be integrated to achieve effective knowledge discovery by involving the best of …

Text visualization becomes an increasingly more important research topic as the need to
understand massive-scale textual information is proven to be imperative for many people …

It is expected that stock prices can be affected by the local and overseas political and
economic events. We extract events from the financial news of Chinese local newspapers …