This paper presents a recommendation algorithm that performs a query dependent random walk on a k-partite graph constructed from the various features relevant to the recommendatio...
Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William...
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
Background: Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been deve...
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
Abstract. This paper shows how multi-dimensional functions, describing the operation of complex equipment, can be learned. The functions are points in a shape space, each produced ...