Range queries in OLAP data cubes
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Managing Intervals Efficiently in Object-Relational Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Worst-Case External-Memory Priority Queues
SWAT '98 Proceedings of the 6th Scandinavian Workshop on Algorithm Theory
Implementing I/O-efficient Data Structures Using TPIE
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Optimal dynamic interval management in external memory
FOCS '96 Proceedings of the 37th Annual Symposium on Foundations of Computer Science
Optimal External Memory Interval Management
SIAM Journal on Computing
Incremental computation and maintenance of temporal aggregates
The VLDB Journal — The International Journal on Very Large Data Bases
Approximate Temporal Aggregation
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Online Amnesic Approximation of Streaming Time Series
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Global distance-based segmentation of trajectories
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Indexable PLA for efficient similarity search
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On computing temporal aggregates with range predicates
ACM Transactions on Database Systems (TODS)
Efficient temporal counting with bounded error
The VLDB Journal — The International Journal on Very Large Data Bases
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
iSAX: indexing and mining terabyte sized time series
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Consistent Top-k Queries over Time
DASFAA '09 Proceedings of the 14th International Conference on Database Systems for Advanced Applications
Online Interval Skyline Queries on Time Series
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Durable top-k search in document archives
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Top-k queries on temporal data
The VLDB Journal — The International Journal on Very Large Data Bases
Discovering influential data objects over time
SSTD'13 Proceedings of the 13th international conference on Advances in Spatial and Temporal Databases
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Ranking temporal data has not been studied until recently, even though ranking is an important operator (being promoted as a first-class citizen) in database systems. However, only the instant top-k queries on temporal data were studied in, where objects with the k highest scores at a query time instance t are to be retrieved. The instant top-k definition clearly comes with limitations (sensitive to outliers, difficult to choose a meaningful query time t). A more flexible and general ranking operation is to rank objects based on the aggregation of their scores in a query interval, which we dub the aggregate top-k query on temporal data. For example, return the top-10 weather stations having the highest average temperature from 10/01/2010 to 10/07/2010; find the top-20 stocks having the largest total transaction volumes from 02/05/2011 to 02/07/2011. This work presents a comprehensive study to this problem by designing both exact and approximate methods (with approximation quality guarantees). We also provide theoretical analysis on the construction cost, the index size, the update and the query costs of each approach. Extensive experiments on large real datasets clearly demonstrate the efficiency, the effectiveness, and the scalability of our methods compared to the baseline methods.