697 search results - page 68 / 140 » Discovering Interesting Subsets Using Statistical Analysis |
IDA
2007
Springer
13 years 10 months ago
2007
Springer
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize th...
WWW
2010
ACM
14 years 2 months ago
2010
ACM
The social sciences strive to understand the political, social, and cultural world around us, but have been impaired by limited access to the quantitative data sources enjoyed by ...
CISS
2008
IEEE
2008
IEEE
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
14 years 4 months ago
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
ICDE
1998
IEEE
14 years 11 months ago
1998
IEEE
Discovery of functionaldependencies from relations has been identified as an important database analysis technique. In this paper, we present a new approach for finding functional...
DASFAA
2010
IEEE
13 years 10 months ago
2010
IEEE
Discovering interesting patterns from high-speed data streams is a challenging problem in data mining. Recently, the support metric-based frequent pattern mining from data stream h...