We propose a framework, called MIC, which adopts an information-theoretic approach to address the problem of quantitative association rule mining. In our MIC framework, we first d...
One important way in which sampling for approximate query processing in a database environment differs from traditional applications of sampling is that in a database, it is feasi...
Ruoming Jin, Leonid Glimcher, Chris Jermaine, Gaga...
In this paper we present a system for automatically integrating unstructured text into a multi-relational database using state-of-the-art statistical models for structure extracti...
Existing techniques to mine periodic patterns in time series data are focused on discovering full-cycle periodic patterns from an entire time series. However, many useful partial ...
In this paper, we present the ArchIS system that achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards. ArchIS&...