Compact Representation of Event Sequences
Nieves Brisaboa, Guillermo de Bernardo, Gonzalo Navarro, Tirso Rodeiro, and
Diego Seco
We introduce a new technique for the efficient management of large sequences
of multi-dimensional data, which takes advantage of regularities that arise in
real-world datasets and supports different types of aggregation queries. More
importantly, our representation is flexible in the sense that the relevant
dimensions and queries may be used to guide the construction process, easily
providing a space-time tradeoff depending on the relevant queries in the
domain. We provide two alternative representations for sequences of
multidimensional data and describe the techniques to efficiently store the
datasets and to perform aggregation queries over the compressed representation.
We perform experimental evaluation on realistic datasets, showing the space
efficiency and query capabilities of our proposal.