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KDD
2008
ACM
217views Data Mining» more  KDD 2008»
16 years 6 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
KDD
2004
ACM
209views Data Mining» more  KDD 2004»
16 years 6 months ago
Tracking dynamics of topic trends using a finite mixture model
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Satoshi Morinaga, Kenji Yamanishi
KDD
2003
ACM
161views Data Mining» more  KDD 2003»
16 years 6 months ago
Empirical Bayesian data mining for discovering patterns in post-marketing drug safety
Because of practical limits in characterizing the safety profiles of therapeutic products prior to marketing, manufacturers and regulatory agencies perform post-marketing surveill...
David M. Fram, June S. Almenoff, William DuMouchel
SIGMOD
2008
ACM
142views Database» more  SIGMOD 2008»
16 years 6 months ago
Cost-based variable-length-gram selection for string collections to support approximate queries efficiently
Approximate queries on a collection of strings are important in many applications such as record linkage, spell checking, and Web search, where inconsistencies and errors exist in...
Xiaochun Yang, Bin Wang, Chen Li
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
16 years 6 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...