The paper addresses the problem of matching and scheduling of DAG-structured application to both minimize the makespan and maximize the robustness in a heterogeneous computing sys...
Abstract. Text documents have sparse data spaces, and nearest neighbors may belong to different classes when using current existing proximity measures to describe the correlation ...
Location models are data structures or knowledge bases used in Ubiquitous Computing for representing and reasoning about spatial relationships between so-called smart objects, i.e....
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...