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Tiffany Wu; Christina Weiland – Society for Research on Educational Effectiveness, 2024
Background/Context: Chronic absenteeism is a serious problem that has been linked to lower academic achievement, diminished socioemotional skills, and an increased likelihood of high school dropout (Allensworth et al., 2021; Gottfried, 2014). As a result, many schools have begun to embrace early warning systems (EWS) as a tool to identify and flag…
Descriptors: Attendance, Early Childhood Education, Intervention, Artificial Intelligence
Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
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Sulyma, Volodymyr; Yaroshenko, Kateryna; Verholaz, Igor; Badyul, Pavlo – International Society for Technology, Education, and Science, 2021
At the examination of a patient, a doctor evaluates clinical picture of the disease that manifests itself by a great number of various general and local symptoms caused by an etiological factor and pathogenesis changes of the different organs and systems of the organism. A purpose of the surgical patient examination is making of early, correct and…
Descriptors: Surgery, Physicians, Clinical Diagnosis, Diseases
Yunxiao Chen; Xiaoou Li; Jingchen Liu; Gongjun Xu; Zhiliang Ying – Grantee Submission, 2017
Large-scale assessments are supported by a large item pool. An important task in test development is to assign items into scales that measure different characteristics of individuals, and a popular approach is cluster analysis of items. Classical methods in cluster analysis, such as the hierarchical clustering, K-means method, and latent-class…
Descriptors: Item Analysis, Classification, Graphs, Test Items
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Feinman, R. D.; Kwok, K. L. – Journal of the American Society for Information Science, 1973
A study was undertaken to classify mechanically a document collection using the free-language words in titles and abstracts of physics research papers. Using a clustering algorithm, results were obtained which closely duplicated clusters obtained by previous experiments with citations. A brief comparison is made with a traditional manual…
Descriptors: Algorithms, Classification, Cluster Analysis, Databases
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Waller, Niels G.; Kaiser, Heather A.; Illian, Janine B.; Manry, Mike – Psychometrika, 1998
The classification capabilities of the one-dimensional Kohonen neural network (T. Kohonen, 1995) were compared with those of two partitioning and three hierarchical cluster methods in 2,580 data sets with known cluster structure. Overall, the performance of the Kohonen networks was similar to, or better than, that of the others. Implications for…
Descriptors: Algorithms, Classification, Cluster Analysis, Comparative Analysis
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Guerrero Bote, Vicente P.; Moya Anegon, Felix de; Herrero Solana, Victor – Information Processing & Management, 2002
Discussion of the classification of documents from bibliographic databases focuses on a method of vectorizing reference documents from LISA (Library and Information Science Abstracts) which permits their topological organization using Kohonen's algorithm. Analyzes possibilities of this type of neural network with respect to the development of…
Descriptors: Algorithms, Bibliographic Databases, Classification, Information Retrieval
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Yu, Clement T. – Journal of the American Society for Information Science, 1974
A clustering algorithm which is tree-like in structure, and is based on user queries, is presented. It is compared to some existing algorithms and is found to be superior. (Author)
Descriptors: Algorithms, Classification, Cluster Analysis, Cluster Grouping
Hoyle, W. G. – Information Storage and Retrieval, 1973
A system of automatic indexing based on Baye's theorem is described briefly. (18 references) (Author)
Descriptors: Algorithms, Automatic Indexing, Bayesian Statistics, Classification
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Morato, Jorge; Llorens, J.; Genova, G.; Moreiro, J. A. – Information Processing & Management, 2003
Discusses the inclusion of contextual information in indexing and retrieval systems to improve results and the ability to carry out text analysis by means of linguistic knowledge. Presents research that investigated whether discourse variables have an impact on information and retrieval and classification algorithms. (Author/LRW)
Descriptors: Algorithms, Classification, Indexing, Information Retrieval
Yu, Clement T. – Information Storage and Retrieval, 1974
Heuristic methods for the construction of term classes are presented and experimental results are obtained to illustrate the usefulness of the method. (Author/PF)
Descriptors: Algorithms, Automatic Indexing, Classification, Cluster Grouping
Bichteler, Julie; Parsons, Ronald G. – Information Storage and Retrieval, 1974
An automatic classification technique using patterns formed by citations in document bibliographies was found to give 62 percent precision and 45 percent recall in a sample file of physics documents. (PF)
Descriptors: Algorithms, Automatic Indexing, Bibliographies, Citations (References)
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Craven, Timothy C. – Journal of Documentation, 1987
Describes a microcomputer-based string index format generated from concept networks using multiple search terms. Link weighting is highlighted as a method to decide which term appears first so the entry reflects the classification implied by the search specification. The computer software used for this system is briefly described. (Author/LRW)
Descriptors: Algorithms, Automatic Indexing, Classification, Computer Software
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Rindskopf, David – Psychometrika, 1992
A general approach is described for the analysis of categorical data when there are missing values on one or more observed variables. The method is based on generalized linear models with composite links. Situations in which the model can be used are described. (SLD)
Descriptors: Algorithms, Classification, Data Analysis, Estimation (Mathematics)
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Mostafa, J.; Lam, W. – Information Processing & Management, 2000
Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…
Descriptors: Algorithms, Classification, Cytology, Evaluation Methods
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