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Katzer, Jeffrey; And Others – 1986
This project examines anaphora (the linguistic device of abbreviated subsequent reference to a concept) in information retrieval (IR) systems in order to develop procedures to recognize anaphors in text and distinguish between anaphoric and non-anaphoric uses of a given term, estimate the number of anaphors appearing in bibliographic records, and…
Descriptors: Abstracts, Algorithms, Classification, Comparative Analysis
PDF pending restorationWhite, Lee J.; And Others – 1975
The major advantage of sequential classification, a technique for automatically classifying documents into previously selected categories, is that the entire document need not be processed before it is classified. This method assumes the availability of a priori categories, a selection of keywords representative of these categories, and the a…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Peer reviewedBall, Stanley – School Science and Mathematics, 1986
Presents a developmental taxonomy which promotes sequencing activities to enhance the potential of matching these activities with learner needs and readiness, suggesting that the order commonly found in the classroom needs to be inverted. The proposed taxonomy (story, skill, and algorithm) involves problem-solving emphasis in the classroom. (JN)
Descriptors: Algorithms, Classification, Cognitive Development, Elementary Education
Borko, Harold; And Others – 1968
Experiments were performed to determine the feasibility of using ALCAPP as one form of on-line dialogue. Assuming the ALCAPP (Automatic List Classification and Profile Production) system is in an on-line mode, investigations of those parameters which could affect its stability and reliability were conducted. Fifty-two full test documents were used…
Descriptors: Abstracts, Algorithms, Analysis of Variance, Automation
Peer reviewedGriffiths, Alan; And Others – Journal of Documentation, 1984
Considers classifications produced by application of single linkage, complete linkage, group average, and word clustering methods to Keen and Cranfield document test collections, and studies structure of hierarchies produced, extent to which methods distort input similarity matrices during classification generation, and retrieval effectiveness…
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping
Peer reviewedWillett, Peter – Information Processing and Management, 1981
Describes a fast algorithm for comparing the lists of terms representing documents in automatic classification experiments. Complexity and running time for the algorithm are compared to other procedures, and a short algol-like routine is presented in the appendix. Eight references are included. (Author/BK)
Descriptors: Algorithms, Automatic Indexing, Classification, Documentation
Kar, B. Gautam; White, Lee J. – 1975
The feasibility of using a distance measure, called the Bayesian distance, for automatic sequential document classification was studied. Results indicate that, by observing the variation of this distance measure as keywords are extracted sequentially from a document, the occurrence of noisy keywords may be detected. This property of the distance…
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
Peer reviewedEnser, P. G. B. – Journal of Documentation, 1985
Investigates techniques for automatic classification of book material focusing on: computer-based surrogation of monographic material, book surrogate clustering on basis of content association, evaluation of resultant classifications. Test collection (250 books) is described with surrogation by means of back-of-the-book index, table of contents,…
Descriptors: Algorithms, Automatic Indexing, Books, Classification
Jonassen, David H.; Hannum, Wallace H. – Journal of Instructional Development, 1986
Describes functions comprising task analysis process--inventory, description, selection, sequencing, and analysis--and reviews distinctions between the micro/macro level, top-down/bottom-up, and job/learning task analysis processes. These functions and distinctions are combined into a quasi-algorithm suggesting which of 30 task analysis procedures…
Descriptors: Algorithms, Behavioral Objectives, Classification, Content Analysis
Cipra, Barry – What's Happening in the Mathematical Sciences, 1993
This document consists of the first two volumes of a new annual serial devoted to surveying some of the important developments in the mathematical sciences in the previous year or so. Mathematics is constantly growing and changing, reaching out to other areas of science and helping to solve some of the major problems facing society. Volumes 1 and…
Descriptors: Algorithms, Biology, Classification, Coding
Cheek, Helen – 1981
Bilingual mathematics competencies and competency-coordinated activities are provided in the four sections of this curriculum guide for kindergarten (pre-operational) and grades 1-3 (concrete-operational) children. Topic areas for kindergarten include: classification (logic); comparing/ordering/graphing; quantitative; measurement; geometry;…
Descriptors: Algorithms, Arithmetic, Bilingual Education Programs, Classification
Peer reviewedPeled, Zimra; And Others – Journal of Educational Computing Research, 1992
Proposes a taxonomy to aid decision makers in selecting computer software consistent with their educational values regarding the nature of instruction and the use of information technology, based on beliefs about human development and learning. Characteristics of instruction, properties of software, and the congruence between them are discussed.…
Descriptors: Algorithms, Classification, Computer Assisted Instruction, Computer Software
Gallagher, Ann M. – 1992
An item classification scheme developed by A. M. Gallagher (1990) was refined, resulting in a more accurate prediction of sex differences in the mathematical sections of the Scholastic Aptitude Test (SAT). Differential Item Functioning (DIF) procedures for examinees scoring over 650 indicated that the majority of items favoring males required the…
Descriptors: Algorithms, Classification, College Entrance Examinations, High Achievement


