The QMUL Team with Probabilistic SQL at Enterprise Track

The enterprise track caught our attention, since the task is similar to a project we carried our for the BBC. Our motivation for participation has been twofold: On one hand, there is the usual challenge to design and test the quality of retrieval strategies. On the other hand, and for us very important, the TREC participation has been an opportunity to investigate the resource effort it requires to deliver a TREC result. Our main findings from this TREC participation are: 1. Through the consequent usage of our probabilistic variant of SQL, we could describe retrieval strategies within a few lines of code. 2. The processing time proved sufficient to deal with the collection. 3. The abstraction-oriented data modelling layers of our HySpirit framework enable relatively junior researches to explore a TREC collection and submit runs. 4. For the less complex retrieval tasks (discussion search, known-item search), minimal resources lead to acceptable results, whereas for the more complex retrieval tasks (expert search), inclusion and combination of all available evidence appear to significantly improve retrieval quality.