Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Fundamentals of speech recognition
Fundamentals of speech recognition
Towards an analysis of range query performance in spatial data structures
PODS '93 Proceedings of the twelfth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Locally adaptive dimensionality reduction for indexing large time series databases
ACM Transactions on Database Systems (TODS)
Efficient Indexing of Spatiotemporal Objects
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Similarity Searching for Multi-Attribute Sequences
SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
On Similarity Queries for Time-Series Data: Constraint Specification and Implementation
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Properties of Embedding Methods for Similarity Searching in Metric Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Signature Technique for Similarity-Based Queries
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Discovering Similar Multidimensional Trajectories
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Indexing multi-dimensional time-series with support for multiple distance measures
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
STRG-Index: spatio-temporal region graph indexing for large video databases
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Towards effective indexing for very large video sequence database
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Action synopsis: pose selection and illustration
ACM SIGGRAPH 2005 Papers
Efficiently Evaluating Order Preserving Similarity Queries over Historical Market-Basket Data
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Indexing spatiotemporal archives
The VLDB Journal — The International Journal on Very Large Data Bases
Global distance-based segmentation of trajectories
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
On the marriage of Lp-norms and edit distance
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Skyline Index for Time Series Data
IEEE Transactions on Knowledge and Data Engineering
Searching trajectories by locations: an efficiency study
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
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
Retrieving k-nearest neighboring trajectories by a set of point locations
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
User oriented trajectory search for trip recommendation
Proceedings of the 15th International Conference on Extending Database Technology
Exploring pattern-aware travel routes for trajectory search
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Efficient Time-Stamped Event Sequence Anonymization
ACM Transactions on the Web (TWEB)
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We study the problem of efficiently evaluating similarity queries on histories, where a history is a d-dimensional time series for d ≥ 1. While there are some solutions for time-series and spatio-temporal trajectories where typically d ≤ 3, we are not aware of any work that examines the problem for larger values of d. In this paper, we address the problem in its general case and propose a class of summaries for histories with a few interesting properties. First, for commonly used distance functions such as the Lp-norm, LCSS, and DTW, the summaries can be used to efficiently prune some of the histories that cannot be in the answer set of the queries. Second, histories can be indexed based on their summaries, hence the qualifying candidates can be efficiently retrieved. To further reduce the number of unnecessary distance computations for false positives, we propose a finer level approximation of histories, and an algorithm to find an approximation with the least maximum distance estimation error. Experimental results confirm that the combination of our feature extraction approaches and the indexability of our summaries can improve upon existing methods and scales up for larger values of d and database sizes, based on our experiments on real and synthetic datasets of 17-dimensional histories.