: The rapid growth of biological databases not only provides biologists with abundant data but also presents a big challenge in relation to the analysis of data. Many data analysis...
Nowadays organizations all over the world are dependent on mining gigantic datasets. These datasets typically contain delicate individual information, which inevitably gets expose...
The ability to distinguish between objects is the fundamental to learning and intelligent behavior in general. The difference between two things is the information we seek; the pr...
Bostjan Brumen, Izidor Golob, Hannu Jaakkola, Tatj...
In this paper, we study the behavior of collaborative filtering based recommendations under evolving user profile scenarios. We propose a systematic validation methodology that ...
Olfa Nasraoui, Jeff Cerwinske, Carlos Rojas, Fabio...
A frequently encountered problem in decision making is the following review problem: review a large number of objects and select a small number of the best ones. An example is sel...
Feature selection is an important task in effective data mining. A new challenge to feature selection is the so-called “small labeled-sample problem” in which labeled data is...
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
High throughput biotechnologies have enabled scientists to collect a large number of genetic and phenotypic attributes for a large collection of samples. Computational methods are...
The term consideration set is used in marketing to refer to the set of items a customer thought about purchasing before making a choice. While consideration sets are not directly ...
Object recognition and content-based image retrieval systems rely heavily on the accurate and efficient identification of shapes. A fundamental requirement in the shape analysis ...
Dragomir Yankov, Eamonn J. Keogh, Li Wei, Xiaopeng...