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A mob of wallabies lies on the brink of starvation when a drought strikes the harsh Australian outback.

Unwilling to endure the conditions any longer, a single wallaby with a bad knee gathers the courage to leave the protection of the mob to seek out a better place.

Joined by two of his closest friends, the trio begin a wild adventure through the perilous and unforgiving land.

Danger follows in every footstep, until they are finally forced to confront their gravest fear...

The dingoes.

Most of the research aimed at counterterrorism, fraud detection, or other forensic applications assumes that this is a specialized application domain for mainstream knowledge discovery. Unfortunately, knowledge discovery changes completely when the datasets being used have been manipulated in order to conceal some underlying activity. Knowledge Discovery for Counterterrorism and Law Enforcement operates from the premise that detection algorithms must be rethought to be effective in this domain, and presents a new approach based on cutting-edge analysis for use in...

High-dimensional spaces arise as a way of modelling datasets with many attributes. Such a dataset can be directly represented in a space spanned by its attributes, with each record represented as a point in the space with its position depending on its attribute values. Such spaces are not easy to work with because of their high dimensionality: our intuition about space is not reliable, and measures such as distance do not provide as clear information as we might expect.

There are three main areas where complex high dimensionality and large datasets arise naturally: data collected by...

Community detection in social networks is an important but challenging problem. This book develops a new technique for finding communities that uses both structural similarity and attribute similarity simultaneously, weighting them in a principled way. The results outperform existing techniques across a wide range of measures, and so advance the state of the art in community detection. Many existing community detection techniques base similarity on either the structural connections among social-network users, or on the overlap among the attributes of each user. Either way loses useful...