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PAKDD
2004
ACM
199views Data Mining» more  PAKDD 2004»
15 years 11 months ago
Temporal Sequence Associations for Rare Events
In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important. Their low occurrence rate in large da...
Jie Chen, Hongxing He, Graham J. Williams, Huidong...
KDD
2000
ACM
114views Data Mining» more  KDD 2000»
15 years 9 months ago
Learning Prosodic Patterns for Mandarin Speech Synthesis
Higher quality synthesized speech is required for widespread use of text-to-speech (TTS) technology, and prosodic pattern is the key feature that makes synthetic speech sound unna...
Yiqiang Chen, Wen Gao, Tingshao Zhu
PVLDB
2010
184views more  PVLDB 2010»
15 years 4 months ago
TimeTrails: A System for Exploring Spatio-Temporal Information in Documents
Spatial and temporal data have become ubiquitous in many application domains such as the Geosciences or life sciences. Sophisticated database management systems are employed to ma...
Jannik Strötgen, Michael Gertz
KDD
2005
ACM
107views Data Mining» more  KDD 2005»
15 years 11 months ago
Predicting the product purchase patterns of corporate customers
This paper describes TIPPPS (Time Interleaved Product Purchase Prediction System), which analyses billing data of corporate customers in a large telecommunications company in orde...
Bhavani Raskutti, Alan Herschtal
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 6 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson