Sequences of events, items, or tokens occurring in an ordered metric space appear often in
data and the requirement to detect and analyze frequent subsequences is a common …

Owing to important applications such as mining web page traversal sequences, many
algorithms have been introduced in the area of sequential pattern mining over the last …

With the growing popularity of shared resources, large volumes of complex data of different
types are collected automatically. Traditional data mining algorithms generally have …

Markov models have been widely used for modelling users' navigational behaviour in the
Web graph, using the transitional probabilities between web pages, as recorded in the web …

This second edition of a bestseller provides up-to-date knowledge of human factors issues
in web design. It comprehensively treats human factors research methods, design …

Discovering associations between elements occurring in a stream is applicable in numerous
applications, including predictive caching and fraud detection. These applications require a …

Finding frequent patterns play an important role in mining association rules, sequences,
episodes, Web log mining and many other interesting relationships among data. Frequent …

The unsupervised detection of anomalies in time series data has important applications in
user behavioral modeling, fraud detection, and cybersecurity. Anomaly detection has, in fact …

Comprehending changes of customer behavior is an essential problem that must be faced
for survival in a fast-changing business environment. Particularly in the management of …

Recommendation algorithms aim at proposing" next" pages to a user based on her current
visit and the past users' navigational patterns. In the vast majority of related algorithms, only …