NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 9 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
Peer reviewed Peer reviewed
Nieto Sanchez, Salvador; Triantaphyllou, Evangelos; Kraft, Donald – Information Processing & Management, 2002
Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)
Descriptors: Algorithms, Cluster Grouping, Comparative Analysis, Mathematical Logic
Peer reviewed Peer reviewed
Miyamoto, S.; Nakayama, K. – Journal of the American Society for Information Science, 1983
A method of two-stage clustering of literature based on citation frequency is applied to 5,065 articles from 57 journals in environmental and civil engineering. Results of related methods of citation analysis (hierarchical graph, clustering of journals, multidimensional scaling) applied to same set of articles are compared. Ten references are…
Descriptors: Algorithms, Citations (References), Civil Engineering, Cluster Analysis
Peer reviewed Peer reviewed
Gordon, Michael D. – Journal of the American Society for Information Science, 1991
Discussion of clustering of documents and queries in information retrieval systems focuses on the use of a genetic algorithm to adapt subject descriptions so that documents become more effective in matching relevant queries. Various types of clustering are explained, and simulation experiments used to test the genetic algorithm are described. (27…
Descriptors: Algorithms, Cluster Grouping, Documentation, Information Retrieval
PDF pending restoration PDF pending restoration
White, 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 reviewed Peer reviewed
Griffiths, 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
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 reviewed Peer reviewed
Can, Fazli – Information Processing and Management, 1994
Discussion of relevancy in information retrieval systems focuses on an analysis of the efficiency of various cluster-based retrieval (CBR) strategies. A method for combining CBR and inverted index search is proposed that is cost effective in terms of time efficiency; and results of experiments are reported. (Contains 32 references.) (LRW)
Descriptors: Algorithms, Cluster Grouping, Comparative Analysis, Cost Effectiveness
Becker, David S.; Pyrce, Sharon R. – 1977
The goal of this project was to find ways of enhancing the efficiency of searching machine readable data bases. Ways are sought to transfer to the computer some of the tasks that are normally performed by the user, i.e., to further automate information retrieval. Four experiments were conducted to test the feasibility of a sequential processing…
Descriptors: Algorithms, Bibliographic Coupling, Cluster Grouping, Computers