In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

Categorical data become increasingly ubiquitous in the modern big data era. In this dissertation, we propose novel statistical learning and inference methods for large-scale categorical data, focusing on latent variable models and their applications to psychometrics. In psychometric assessments, the subjects' underlying aptitude often cannot be…

The intent of this paper is to generalize the min and max clustering procedures in such a way that the assumption of a symmetric similarity measure is unnecessary. (Author)

The purpose of this study was to compare three technologies: the item forms technology (domain-referenced testing) of Hively et al. (1968), the hierarchical or stratified item forms technology of Ferguson (1969), and the algorithmic technology of Scandura (1971, 1973). (Author/RK)

A method of nonmetric multidimensional scaling is described which minimizes pairwise departures from monotonicity. (Author)

Local increases in fundamental frequency (Fo) and large integrals of energy in the syllabic nucleus are known to be among the best acoustical correlates of stress. Major syntactic constituents have been shown to have archetype rapid-rise-then-gradual-fall Fo contours, with the rise into the maximum Fo often associated with the first stressed…