We propose a framework for mobile advertising covering Value-Added Services where an ad-database is maintained on the device and both selection and display are dictated by the device. Advantages over existing mobile marketing are that ads are more timely, viable on a variety of use cases, can be both location-sensitive and personalized with minimal privacy concerns, and provide an obvious means for subsidizing users' service costs. We construct a suitable selection algorithm and evaluate its execution, accuracy and scalability. We show that ad-serving can be done under the processing constraints imposed by mobiles, which may lead to improvements in mobile marketing effectiveness.

We present an approach for discovery of groups of unusual data points that are anomalous for similar reasons. This differs from clustering in that the points that are grouped may be quite 'distant' and can use categorical attributes, and differs from anomaly detection in that we are not looking for individual outliers.

Collaborative tagging is the aggregate effort by a community of online users to annotate web content with metadata labels called tags. It is a simple activity that enriches our knowledge about digital content, and has gained popularity with services such as Del.icio.us. Del.icio.us has a large repository that evolves daily, presenting interesting new problems for IR. We present TagScore, a scoring function to rate the goodness of Del.icio.us tags for their associated web page. It gives us a succinct synopsis for a page that we can use to efficiently find similar pages. Using real Del.icio.us data, we show that our approach gives good correlation to cosine similarity but is several hundred times faster and requires minimal storage overhead.

Social tagging describes a community of users labeling web content with tags. It is a simple activity that enriches our knowledge about resources on the web. For a computer to help users search the tagged repository, it must know when tags are good or bad. We describe TagScore, a scoring function that rates the goodness of tags. The tags and their ratings give us a succinct synopsis for a page. We `find similar' pages in Del.icio.us by comparing synopses. Our approach gives good correlation to the full cosine similarity but is hundreds of times faster.

New means of communication are constantly emerging, some of which may constitute resource misuse of an organisation's network system. Identifying the protocols used is straight-forward when inspecting network logs, but we focus on the problem of identifying the underlying protocol present in an unknown TCP connection. Actions are difficult to detect if the underlying protocol is encrypted and tunneled through a proxy server or SSH. We use a graph-comparison approach to build profiles of several protocols, and attempt to classify an unknown, encrypted protocol against these profiles using only the visible behaviour of the protocol being tunneled - the size, timing and direction of packets