People use weblogs to express thoughts, present ideas and share knowledge, therefore weblogs are extraordinarily valuable resources, amongs others, for trend analysis. Trends are derived from the chronological sequence of blog post count per topic. The comparison with a reference corpus allows qualitative statements over identified trends. We propose a crosslanguage blog mining and trend visualisation system to analyse blogs across languages and topics. The trend visualisation facilitates the identification of trends and the comparison with the reference news article corpus. To prove the correctness of our system we computed the correlation between trends in blogs and news articles for a subset of blogs and topics. The evaluation corroborated our hypothesis of a high correlation coefficient for these subsets and therefore

In this paper we present the building blocks of our semi-automatic annotation tool which supports multi-modal and multi-level annotation of meetings. The main focus is on the proper design and functionality of the modules for recognizing meeting actions. The key features, identity and position of the speakers, are provided by different modalities (audio and video). Three audio algorithms (voice activity detection, speaker identification and direction of arrival) and three video algorithms (detection, tracking and identification) form the low-level feature extraction components. Low-level features are automatically merged and the recognized actions are proposed to the user by visualizing them. The annotation labels are related but not limited to events during meetings. The user can finally confirm or if necessary, modify the suggestion, and then store the actions into a database