Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
We introduce a new data mining problem: mining truth tables in binary datasets. Given a matrix of objects and the properties they satisfy, a truth table identifies a subset of pr...
Clifford Conley Owens III, T. M. Murali, Naren Ram...
DTA (Decoupled Threaded Architecture) is designed to exploit fine/medium grained Thread Level Parallelism (TLP) by using a distributed hardware scheduling unit and relying on exi...