Dynamic programming algorithm optimization for spoken word recognition
Readings in speech recognition
Temporal databases: theory, design, and implementation
Temporal databases: theory, design, and implementation
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
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
| Hi-index | 0.00 |
The Relaxed-Periodicity Pattern describes loose-cyclic behavior of objects while allowing uneven stretch or shrink on time axis, limited noises, and inflation /deflation of attribute values. To discover Relaxed-Periodicity from Temporal Databases, we propose the concepts of Attribute Trend, Trend Inertia, Peak-Valley Pattern, Inertia Algorithm with Anti-noise ability, as well as the Peak-Valley Algorithm, and show that the implementation prototype is efficient.