Deriving Summaries Through an Identity-Based Approach

May 2000

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

Volume

Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2000)

All Papers

The existence of large datasets requires methods for producing simpler or summarized views of data. Typical approaches to summarization based on statistics do not capture completely the semantics associated with coarser views of spatio-temporal phenomena. In this paper, methods for deriving summaries of spatio-temporal objects are described and a set of operators is introduced for evolving summarized views. The approach uses the concept of object identity and examines the nature of deriving coarser views of objects based on changes to temporal detail as well as eliminating and combining objects.