databases that are updated through continuous insertion queries.
In social networks, users post text, images or videos and annotate each of them with a set of tags describing its content. We define sets of co-occurring tags to represent topics and track the correlations of co-occurring tags over time. We split the tags to multiple nodes and make each node responsible of computing the correlations of its assigned tags. We implemented our approach in Storm, a distributed processing engine, and conducted a user study to estimate the quality of our results.
In structured data stored in relational databases, top-k group-by queries are defined and an emerging topic is considered to be a change in the top-k results. We maintain the top-k result sets in the presence of updates minimizing the interaction with the underlying database. We implemented and experimentally tested our approach.