Collaborative filtering (CF) is an important and popular technology for recommender
systems. However, current CF methods suffer from such problems as data sparsity …

This paper identifies, by means of video and Kinect data, a set of predictors that estimate the
presentation skills of 448 individual students. Two evaluation criteria were predicted: eye …

The learning algorithm for multivariable data analysis (LAMDA) is a learning method to
group or classify quantitative and qualitative historical data. LAMDA can be applied for self …

Cognitive psychology works have shown that the cognitive representation of categories is
based on a typicality notion: all objects of a category do not have the same …

In recent years, the interpretation of scalar terms in embedded environments has been
investigated extensively. Some experimentalists have been concerned with sentences like …

The idea of a fuzzy set is formally modeled by a membership function that plays the same
role as the characteristic function for an ordinary set, except that the membership function …

In recent years, as the installed capacity of distributed generation (DG) and the penetration
level continue to increase, the uncertainties of the DGs like photovoltaic (PV) generation …

With the rapid growth of “Web of Things”(WoT), there is a pressing need to develop effective
mechanisms for the intelligent discovery and selection of these things (items) …

This chapter focuses on real-world applications of fuzzy techniques for information retrieval
and data mining. It gives a presentation of the theoretical background common to all …

Typicality degrees were defined in supervised learning as a tool to build characteristic
representatives for data categories. In this paper, an extension of these typicality degrees to …