TSP
2008
13 years 9 months ago
2008
A new hierarchical nonparametric Bayesian framework is proposed for the problem of multi-task learning (MTL) with sequential data. The models for multiple tasks, each characterize...
IDA
2008
Springer
13 years 11 months ago
2008
Springer
Abstract. We address the problem of matching imperfectly documented schemas of data streams and large databases. Instancelevel schema matching algorithms identify likely correspond...
FPL
2008
Springer
14 years 12 days ago
2008
Springer
Association Rules Mining (ARM) algorithms are designed to find sets of frequently occurring items in large databases. ARM applications have found their way into a variety of field...
VLDB
1995
ACM
14 years 2 months ago
1995
ACM
Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an effic...
KDD
1995
ACM
14 years 2 months ago
1995
ACM
Techniques for learning from data typically require data to be in standard form. Measurements must be encoded in a numerical format such as binary true-or-false features, numerica...
PODS
1998
ACM
14 years 3 months ago
1998
ACM
The problem of finding association rules in a large database of sales transactions has been widely studied in the literature, We discuss some of the weaknessesof the large itemset...
SIGMETRICS
2000
ACM
14 years 3 months ago
2000
ACM
This paper presents an analytical model to study how working sets scale with database size and other applications parameters in decision-support systems (DSS). The model uses appl...
DEXAW
2000
IEEE
14 years 3 months ago
2000
IEEE
In this paper we explore the applicability of an algorithm designed for finding association rules in large databases to the discovery of relevant associations from a large case ba...
SBACPAD
2003
IEEE
14 years 4 months ago
2003
IEEE
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
ICDM
2003
IEEE
14 years 4 months ago
2003
IEEE
Pattern-based clustering is important in many applications, such as DNA micro-array data analysis, automatic recommendation systems and target marketing systems. However, pattern-...