Evaluating Centering for Information Ordering Using Corpora

In this article we discuss several metrics of coherence defined using centering theory and investigate the usefulness of such metrics for information ordering in automatic text generation. We estimate empirically which is the most promising metric and how useful this metric is using a general methodology applied on several corpora. Our main result is that the simplest metric (which relies exclusively on NOCB transitions) sets a robust baseline that cannot be outperformed by other metrics which make use of additional centering-based features. This baseline can be used for the development of both text-to-text and concept-to-text generation systems. </jats:p

So what can we actually do with content-based video retrieval?

In this talk I will give a roller-coaster survey of the state of the art in automatic video analysis, indexing, summarisation, search and browsing as demonstrated in the annual TRECVid benchmarking evaluation campaign. I will concentrate on content-based techniques for video management which form a complement to the dominant paradigm of metadata or tag-based video management and I will use example techniques to illustrate these