KDD
2002
ACM
14 years 5 months ago
2002
ACM
Support vector machines (SVMs) excel at two-class discriminative learning problems. They often outperform generative classifiers, especially those that use inaccurate generative m...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
We present a framework for mining association rules from transactions consisting of categorical items where the data has been randomized to preserve privacy of individual transact...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
When automatically extracting information from the world wide web, most established methods focus on spotting single HTMLdocuments. However, the problem of spotting complete web s...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
A key challenge facing IT organizations today is their evolution towards adopting e-business practices that gives rise to the need for reengineering their underlying software syst...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
In this paper we investigate the general problem of discovering recurrent patterns that are embedded in categorical sequences. An important real-world problem of this nature is mo...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
KDD
2002
ACM
14 years 5 months ago
2002
ACM
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...