The EUMSSI project (Event Understanding through Multimodal Social Stream Interpretation) aims at developing technologies for aggregating data presented as unstructured information in sources of very different nature. The multimodal analytics will help organize, classify and cluster cross-media streams, by enriching its associated metadata in an interactive manner, so that the data resulting from analysing one media helps reinforce the aggregation of information from other media, in a cross-modal semantic representation framework. Once all the available descriptive information has been collected, an interpretation component will dynamically reason
over the semantic representation in order to derive implicit knowledge. Finally the enriched information will be fed to a hybrid recommendation system, which will be at the basis of two well-motivated use-cases. In this paper we give a brief overview of EUMSSI¿s main goals and how we are approaching its implementation using UIMA to integrate and combine various layers of annotations coming from different sources.
Grivolla J, Melero M, Badia T, Cabulea C, Welle D, Esteve Y, Le Mans F, Herder E, Odobez JM, Preub S. EUMSSI: a Platform for Multimodal Analysis and Recommendation using UIMA. Dins: AA.VV.. Proceedings of COLING 2014. 1 ed. ACL; 2014.