The complexity of next-generation retrieval systems originates from the requirement to organise massive and ever growing volumes of heterogeneous data and meta-data, together with the need to provide distributed management prevalently based on similarity matching. The problem starts with data acquisition of weakly structured or completely unstructured data, such as images and video, which necessarily need innovative techniques for information extraction and classification to increase their findability.
In principle, we consider search and object findability as two principle and synergic aspects of retrieval. They both pose the effectiveness and efficiency challenges which need innovative theories and technologies, and must be studied together to converge to qualitatively new retrieval tools of the future. Fundamental to our approach is the development of scalable solutions.