A load shedding framework for XML stream joins
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I
A layered approach to revisitation prediction
ICWE'11 Proceedings of the 11th international conference on Web engineering
Online activity graph for document importance and association
Proceedings of the 7th International Conference on Semantic Systems
Processing continuous text queries featuring non-homogeneous scoring functions
Proceedings of the 21st ACM international conference on Information and knowledge management
Reverb: recommending code-related web pages
Proceedings of the 2013 International Conference on Software Engineering
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Temporal data analysis in data warehouses and datastreaming systems often uses time decay to reduce the importance of older tuples, without eliminating their influence, on the results of the analysis. While exponential time decay is commonly used in practice, other decay functions (e.g. polynomial decay) are not, even though they have been identified as useful. We argue that this is because the usual definitions of time decay are "backwards": the decayed weight of a tuple is based on its age, measured backward from the current time. Since this age is constantly changing, such decay is too complex and unwieldy for scalable implementation. In this paper, we propose a new class of "forward" decay functions based on measuring forward from a fixed point in time. We show that this model captures the more practical models already known, such as exponential decay and landmark windows, but also includes a wide class of other types of time decay. We provide efficient algorithms to compute a variety of aggregates and draw samples under forward decay, and show that these are easy to implement scalably. Further, we provide empirical evidence that these can be executed in a production data stream management system with little or no overhead compared to the undecayed computations. Our implementation required no extensions to the query language or the DSMS, demonstrating that forward decay represents a practical model of time decay for systems that deal with time-based data.