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SIGMOD
2005
ACM
150views Database» more  SIGMOD 2005»
16 years 5 months ago
BRAID: Stream Mining through Group Lag Correlations
The goal is to monitor multiple numerical streams, and determine which pairs are correlated with lags, as well as the value of each such lag. Lag correlations (and anticorrelation...
Yasushi Sakurai, Spiros Papadimitriou, Christos Fa...
APWEB
2008
Springer
15 years 7 months ago
Mining, Ranking, and Using Acronym Patterns
Techniques for being able to automatically identify acronym patterns are very important for enhancing a multitude of applications that rely upon search. This task is challenging, d...
Xiaonan Ji, Gu Xu, James Bailey, Hang Li
152
Voted
JDWM
2010
139views more  JDWM 2010»
15 years 3 months ago
Mining Frequent Generalized Patterns for Web Personalization in the Presence of Taxonomies
The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usagebased approach to generate recommendations that ...
Panagiotis Giannikopoulos, Iraklis Varlamis, Magda...
152
Voted
BMCBI
2010
144views more  BMCBI 2010»
15 years 5 months ago
Graph-based clustering and characterization of repetitive sequences in next-generation sequencing data
Background: The investigation of plant genome structure and evolution requires comprehensive characterization of repetitive sequences that make up the majority of higher plant nuc...
Petr Novák, Pavel Neumann, Jirí Maca...
KDD
2005
ACM
124views Data Mining» more  KDD 2005»
16 years 5 months ago
CLICKS: an effective algorithm for mining subspace clusters in categorical datasets
We present a novel algorithm called Clicks, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, Clicks mines subs...
Mohammed Javeed Zaki, Markus Peters, Ira Assent, T...