The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 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
The string B-tree: a new data structure for string search in external memory and its applications
Journal of the ACM (JACM)
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
Searching Multimedia Databases by Content
Searching Multimedia Databases by Content
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The TV-tree: an index structure for high-dimensional data
The VLDB Journal — The International Journal on Very Large Data Bases - Spatial Database Systems
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
The A-tree: An Index Structure for High-Dimensional Spaces Using Relative Approximation
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
The X-tree: An Index Structure for High-Dimensional Data
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On the need for time series data mining benchmarks: a survey and empirical demonstration
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Independent Quantization: An Index Compression Technique for High-Dimensional Data Spaces
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Warping indexes with envelope transforms for query by humming
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
High Performance Discovery In Time Series: Techniques And Case Studies (Monographs in Computer Science)
Semantic similarity between search engine queries using temporal correlation
WWW '05 Proceedings of the 14th international conference on World Wide Web
Measuring the meaning in time series clustering of text search queries
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Exact indexing of dynamic time warping
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
iSAX: indexing and mining terabyte sized time series
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
iSAX: disk-aware mining and indexing of massive time series datasets
Data Mining and Knowledge Discovery
Optimal distance bounds for fast search on compressed time-series query logs
ACM Transactions on the Web (TWEB)
Sublinear querying of realistic timeseries and its application to human motion
Proceedings of the international conference on Multimedia information retrieval
Exact indexing for massive time series databases under time warping distance
Data Mining and Knowledge Discovery
Replication mechanisms for a distributed time series storage and retrieval service
Proceedings of the 8th ACM international conference on Autonomic computing
Scalable kNN search on vertically stored time series
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient processing of multiple DTW queries in time series databases
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Scalable similarity search of timeseries with variable dimensionality
Proceedings of the 20th ACM international conference on Information and knowledge management
SFA: a symbolic fourier approximation and index for similarity search in high dimensional datasets
Proceedings of the 15th International Conference on Extending Database Technology
PA-Miner: process analysis using retrieval, modeling, and prediction
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Searching and mining trillions of time series subsequences under dynamic time warping
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Computing Surveys (CSUR)
ACM Transactions on Knowledge Discovery from Data (TKDD) - Special Issue on ACM SIGKDD 2012
Monitoring and diagnosing indicators for business analytics
CASCON '13 Proceedings of the 2013 Conference of the Center for Advanced Studies on Collaborative Research
Discovering longest-lasting correlation in sequence databases
Proceedings of the VLDB Endowment
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Continuous growth in sensor data and other temporal data increases the importance of retrieval and similarity search in time series data. Efficient time series query processing is crucial for interactive applications. Existing multidimensional indexes like the R-tree provide efficient querying for only relatively few dimensions. Time series are typically long which corresponds to extremely high dimensional data in multidimensional indexes. Due to massive overlap of index descriptors, multidimensional indexes degenerate for high dimensions and access the entire data by random I/O. Consequently, the efficiency benefits of indexing are lost. In this paper, we propose the TS-tree (time series tree), an index structure for efficient time series retrieval and similarity search. Exploiting inherent properties of time series quantization and dimensionality reduction, the TS-tree indexes high-dimensional data in an overlap-free manner. During query processing, powerful pruning via quantized separator and meta data information greatly reduces the number of pages which have to be accessed, resulting in substantial speed-up. In thorough experiments on synthetic and real world time series data we demonstrate that our TS-tree outperforms existing approaches like the R*-tree or the quantized A-tree.