Sciweavers

349 search results - page 6 / 70
» Online Data Mining for Co-Evolving Time Sequences
Sort
View
GRC
2010
IEEE
13 years 8 months ago
Local Pattern Mining from Sequences Using Rough Set Theory
Abstract--Sequential pattern mining is a crucial but challenging task in many applications, e.g., analyzing the behaviors of data in transactions and discovering frequent patterns ...
Ken Kaneiwa, Yasuo Kudo
KDD
2012
ACM
217views Data Mining» more  KDD 2012»
11 years 9 months ago
The long and the short of it: summarising event sequences with serial episodes
An ideal outcome of pattern mining is a small set of informative patterns, containing no redundancy or noise, that identifies the key structure of the data at hand. Standard freq...
Nikolaj Tatti, Jilles Vreeken
KDD
2003
ACM
129views Data Mining» more  KDD 2003»
14 years 7 months ago
Online novelty detection on temporal sequences
: Novelty detection, or anomaly detection, on temporal sequences has increasingly attracted attention from researchers in different areas. In this paper, we present a new framework...
Junshui Ma, Simon Perkins
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
13 years 11 months ago
Mining asynchronous periodic patterns in time series data
Periodicy detection in time series data is a challenging problem of great importance in many applications. Most previous work focused on mining synchronous periodic patterns and d...
Jiong Yang, Wei Wang 0010, Philip S. Yu
EUSFLAT
2007
105views Fuzzy Logic» more  EUSFLAT 2007»
13 years 8 months ago
SPoID: Do Not Throw Meaningful Incomplete Sequences Away!
Industrial databases often contain a large amount of unfilled information. During the knowledge discovery process one processing step is often necessary in order to remove these ...
Céline Fiot, Anne Laurent, Maguelonne Teiss...