Presents an efficient text categorization (or text classification) algorithm for document retrieval of natural language texts that generates bigrams (two-word phrases) and uses the information gain metric, combined with various frequency thresholds. Experimental results suggest that the bigrams can substantially raise the quality of feature sets.…

Discussion of automated information services focuses on information classification and collaborative agents, i.e. intelligent computer programs. Highlights include multi-agent systems; distributed artificial intelligence; thesauri; document representation and classification; agent modeling; acquaintances, or remote agents discovered through…

Discussion of knowledge management for electronic data focuses on creating a high quality similarity ranking algorithm. Topics include similarity ranking and unstructured data management; searching, categorization, and summarization of documents; query evaluation; considering sentences in addition to keywords; and vector models. (LRW)

Develops and analyzes four algorithms for feature selection in the context of rough set methodology. Experimental results confirm the expected relationship between the time complexity of these algorithms and the classification accuracy of the resulting upper classifiers. When compared, results of upper classifiers perform better than lower…

A method for robust canonical discriminant analysis via two robust objective loss functions is discussed. Majorization is used at several stages in the minimization procedure to obtain a monotonically convergent algorithm. A simulation study and empirical data illustrate the procedure. (SLD)

An algorithm based on the majorization theory of J. de Leeuw and W. J. Heiser is presented for fitting the slide-vector model. It views the model as a constrained version of the unfolding model. A three-way variant is proposed, and two examples from market structure analysis are presented. (SLD)

Presents a mathematical theory that can be used to define concentration places of objects within unordered classes. The application to research on the evolution of journals and subject areas is illustrated, and an online method of calculating concentration evolution is described. (1 references) (CLB)

Evaluates the retrieval performance of an algorithm that automatically categorizes medical documents, which consists in assigning an International Code of Disease (ICD) based on well-known information retrieval techniques. Reports on experimental results that tested precision using a database of over 20,000 medical documents. (Author/LRW)

Two papers are included as Part Four of this report on Salton's Magical Automatic Retriever of Texts (SMART) project report. The first paper: "A Controlled Single Pass Classification Algorithm with Application to Multilevel Clustering" by D. B. Johnson and J. M. Laferente presents a single pass clustering method which compares favorably…

Investigates the feasibility of using a distance measure for automatic sequential document classification. This property of the distance measure is used to design a sequential classification algorithm which classifies key words and analyzes them separately in order to assign primary and secondary classes to a document. (VT)

Reviews aspects of the relationship between machine learning and information retrieval. Highlights include learning programs that extend from knowledge-sparse learning to knowledge-rich learning; the role of the thesaurus; knowledge bases; artificial intelligence; weighting documents; work frequency; and merging classification structures. (78…

This study is a critical evaluation of the roles for coding and scoring of missing responses to multiple-choice items in educational tests. The focus is on tests in which the test-takers have little or no motivation; in such tests omitting and not reaching (as classified by the currently adopted operational rules) is quite frequent. Data from the…

Reviews the potential and methodology of applying grouping algorithms and methodology of applying grouping algorithms to problems in educational research and practice. (JLB)

Large-scale, on-line information storage and retrieval systems pose numerous problems above those encountered by smaller systems. A step toward the solution of these problems is presented along with several demonstrations of feasibility and advantages. The methodology on which this solution is based is that of a posteriori automatic classification…

The application of the "back-propagation" learning algorithm to the task of determining the right set of features corresponding to the words in an input sentence is described. Features that are specific to particular nouns and verbs, that indicate whether a nominal constituent is singular or plural, definite or indefinite, and that…