Beyond uniformity and independence: analysis of R-trees using the concept of fractal dimension
PODS '94 Proceedings of the thirteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Self-spacial join selectivity estimation using fractal concepts
ACM Transactions on Information Systems (TOIS)
Data structures and algorithms for nearest neighbor search in general metric spaces
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Some approaches to best-match file searching
Communications of the ACM
ACM Computing Surveys (CSUR)
The TSQL2 Temporal Query Language
The TSQL2 Temporal Query Language
Modern Information Retrieval
Fast Indexing and Visualization of Metric Data Sets using Slim-Trees
IEEE Transactions on Knowledge and Data Engineering
M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Research Issues in Spatio-temporal Database Systems
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
The Metric Histogram: A New and Efficient Approach for Content-based Image Retrieval
Proceedings of the IFIP TC2/WG2.6 Sixth Working Conference on Visual Database Systems: Visual and Multimedia Information Management
Distance Exponent: A New Concept for Selectivity Estimation in Metric Trees
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
SINA: scalable incremental processing of continuous queries in spatio-temporal databases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
The Amsterdam Library of Object Images
International Journal of Computer Vision
Indexing mobile objects using dual transformations
The VLDB Journal — The International Journal on Very Large Data Bases
Conceptual partitioning: an efficient method for continuous nearest neighbor monitoring
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
ST2B-tree: a self-tunable spatio-temporal b+-tree index for moving objects
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Predictive Join Processing between Regions and Moving Objects
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Continuous Clustering of Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Continuous k-Means Monitoring over Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Continuous Intersection Joins Over Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Continuous monitoring of exclusive closest pairs
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Continuous medoid queries over moving objects
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
BM+-Tree: a hyperplane-based index method for high-dimensional metric spaces
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Hi-index | 0.00 |
Recent advances in information technology demand handling complex data types, such as images, video, audio, time series and genetic sequences. Distinctly from traditional data (such as numbers, short strings and dates), complex data do not possess the total ordering property, yielding relational comparison operators useless. Even equality comparisons are of little help, as it is very unlikely to have two complex elements exactly equal. Therefore, the similarity among elements has emerged as the most important property for comparisons in such domains, leading to the growing relevance of metric spaces to data search. Regardless of the data domain properties, the systems need to track evolution of data over time. When handling multidimensional data, temporal information is commonly treated as just one or more dimensions. However, metric data do not have the concept of dimensions, thus adding a plain "temporal dimension" does not make sense. In this paper we propose a novel metric-temporal data representation and exploit its properties to compare elements by similarity taking into account time-related evolution. We also present experimental evaluation, which confirms that our technique effectively takes into account the contributions of both the metric and temporal data components. Moreover, the experiments showed that the temporal information always improves the precision of the answer.