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IDA
2007
Springer
15 years 6 months ago
Approximate mining of frequent patterns on streams
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
Claudio Silvestri, Salvatore Orlando
PRL
2010
205views more  PRL 2010»
15 years 1 months ago
Mining outliers with faster cutoff update and space utilization
It is desirable to find unusual data objects by Ramaswamy et al's distance-based outlier definition because only a metric distance function between two objects is required. It...
Chi-Cheong Szeto, Edward Hung
CINQ
2004
Springer
125views Database» more  CINQ 2004»
15 years 12 months ago
Deducing Bounds on the Support of Itemsets
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation however, is very data intensive and sometimes produces a prohibitively large output. I...
Toon Calders
KDD
2001
ACM
150views Data Mining» more  KDD 2001»
16 years 7 months ago
Empirical bayes screening for multi-item associations
This paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item s...
William DuMouchel, Daryl Pregibon
ICAI
2010
15 years 4 months ago
Using Sensor Sequences for Activity Recognition by Mining and Multi-Class Adaboost
- In this paper, we present an activity recognition system using sensor sequence information generated from many binary on-off state sensors. When many sensors are deployed the num...
Md. Kamrul Hasan, Sungyoung Lee, Young-Koo Lee