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…

Presents a relevance-feedback strategy that improves the effectiveness of information-retrieval systems based on back-propagation of the relevance of retrieved documents using an algorithm developed in a neural approach. Describes a neural information-retrieval model and reports results obtained with the algorithm in three different environments.…

Presents an interpolation methodology that duplicates and improves the results of mathematical functional relationships useful for designing business enterprise simulations and argues that interpolation is effective over the entire range of production and sales activity. (six references) (EA)

This paper offers a new methodology for analyzing individual differences in preference judgments with regard to a set of stimuli. (Author)

The Hepatitis Knowledge Base (text of prototype information system) was used for modifying and testing "A Navigator of Natural Language Organized (Textual) Data" (ANNOD), a retrieval system which combines probabilistic, linguistic, and empirical means to rank individual paragraphs of full text for similarity to natural language queries…

Reviews the development and the principal elements of total quality management (TQM) and demonstrates methods for introducing some of the key elements into a strategy-oriented business simulation game that can be used to teach future managers. Topics discussed include increased focus on the customer; continuous improvement; and competitive…

Proposes a new learning algorithm to improve the retrieval effectiveness of the search system used in the hypertext environment using an extended Boolean model with links to improve the ranking of retrieved items. Highlights include the basic retrieval scheme, the learning scheme, and a review of basic probabilistic retrieval models. (Contains 32…

Discusses the results of modeling the performance of searching large text databases via various parallel hardware architectures and search algorithms. The performance under load and the cost of each configuration are compared, and a common search workload used in the modeling is described. (Contains 26 references.) (LRW)

Discussion of instructional design models focuses on a study concerned with developing effective instruction in heuristic-based problem solving for computer programing. Highlights include distinctions between algorithms and heuristics; pretests and posttests; revised instructional design procedures; student attitudes; task analysis; and…

The six papers that comprise this document deal with topics related to the National Institute for Occupational Safety and Health (NIOSH) and/or its online document retrieval system, NIOSHTIC. Specific subjects include: (1) a method to catalog multiple sources of NIOSH publications for dissemination; (2) an input rejection algorithm used to provide…