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Singelmann, Lauren Nichole – ProQuest LLC, 2022
To meet the national and international call for creative and innovative engineers, many engineering departments and classrooms are striving to create more authentic learning spaces where students are actively engaging with design and innovation activities. For example, one model for teaching innovation is Innovation-Based Learning (IBL) where…
Descriptors: Engineering Education, Design, Educational Innovation, Models
Ashley Haigler – ProQuest LLC, 2021
The results of an industry research survey showed, understanding Dissertation Research categories has not been the focused on many researchers and institutions. This research expands on machine learning methodologies using two similar datasets to answer these three questions: 1. Is there a way to track the trends of Pace University's Doctor of…
Descriptors: Artificial Intelligence, Content Analysis, Cluster Grouping, Classification

Boreham, Jillian; Niblett, Bryan – Information Processing and Management, 1976
A suite of computer programs has been developed for representing the full text of lengthy documents in vector form and classifying them by a clustering method. (Author)
Descriptors: Classification, Cluster Grouping, Computer Programs, 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

Yu, C. T. – Journal of the American Society for Information Science, 1976
A measure for the quantification of the changes in classification under small changes in data is proposed. (Author)
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Information Retrieval
Gerson, Gordon M. – Information Storage and Retrieval, 1972
Patents are clustered by similar cited-by" patterns using MacQueen's algorithm. The clusters are enriched by the addition of citing patents. These maximally connected clusters, or cliques, form the classification. (27 references) (Author)
Descriptors: Classification, Cluster Grouping, Computers, Information Retrieval

Swanson, Rowena W. – Journal of the American Society for Information Science, 1973
An important factor to be considered in applying clustering techniques to information storage and retrieval problems is the use to be made of the resultant groupings. An examination of cluster criteria differentiation as a function of purpose may be fruitful in the exploitation of clustering techniques. (12 references) (Author/KE)
Descriptors: Classification, Cluster Grouping, Information Retrieval, Information Science

Harding, Alan F.; Willett, Peter – Journal of the American Society for Information Science, 1980
Demonstrates that the process of comparing each document in an automated system with all others during the classification procedure may be avoided by the use of an inverted file. (FM)
Descriptors: Automatic Indexing, Classification, Cluster Grouping, Information Retrieval

Van Rijsbergen, C. J.; Croft, W. B. – Information Processing and Management, 1975
The single-link cluster method is used to construct a hierarchic classification for the 1400 documents in the Cranfield test collection. A variety of retrieval strategies applied to this hierarchy are evaluated in terms of effectiveness and efficiency. (Author)
Descriptors: Classification, Cluster Grouping, Efficiency, Information Retrieval
van Rijsbergen, C. J. – Information Storage and Retrieval, 1974
Reports the results of experiments in document clustering using three well-known test collections. (Author)
Descriptors: Classification, Cluster Grouping, Evaluation Methods, Information Retrieval
Ball, Geoffrey H. – 1970
Sorting things into groups is a basic intellectual task that allows people to simplify with minimal reduction in information. Classification techniques, which include both clustering and discrimination, provide step-by-step computer-based procedures for sorting things based on notions of generalized similarity and on the "class description"…
Descriptors: Classification, Cluster Grouping, Computers, Correlation
Cornell Univ., Ithaca, NY. Dept. of Computer Science. – 1970
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…
Descriptors: Algorithms, Automation, Classification, Cluster Grouping

Frants, Valery I.; And Others – Information Processing and Management, 1993
Shows how to automatically construct a classification of users and a clustering of documents and cross-references among clusters based on users' information needs. Feedback in the construction of this classification and clustering that allows for the classification to be changed to reflect changing needs of users is also described. (22 references)…
Descriptors: Classification, Cluster Analysis, Cluster Grouping, Expert Systems
CHIEN, R.T.; PREPARATA, F.P. – 1967
ONE OF THE PROBLEMS ENCOUNTERED IN CLUSTERING TECHNIQUES AS APPLIED TO DOCUMENT RETRIEVAL SYSTEMS USING BIBLIOGRAPHIC COUPLING DEVICES IS THAT THE COMPUTATIONAL EFFORT REQUIRED GROWS ROUGHLY AS THE SQUARE OF THE COLLECTION SIZE. IN THIS STUDY GRAPH THEORY IS APPLIED TO THIS PROBLEM BY FIRST MAPPING THE CITATION GRAPH OF THE DOCUMENT COLLECTION…
Descriptors: Algorithms, Bibliographic Coupling, Classification, Cluster Grouping

Boley, Daniel; Gini, Maria; Hastings, Kyle; Mobasher, Bamshad; Moore, Jerry – Internet Research, 1998
Describes WebACE, the architecture of a client-side agent that explores and classifies Web documents in clusters automatically and discusses the details of the algorithms within its key components. Highlights principal direction divisive partitioning (PDDP), a scalable hierarchical clustering algorithm; compares it to other clustering methods; and…
Descriptors: Algorithms, Automation, Classification, Cluster Grouping
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