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| Main Authors: | , |
|---|---|
| Format: | Recurso educativo Open Access |
| Language: | en |
| Published: |
2001
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| Subjects: | |
| Online Access: | https://eric.ed.gov/?id=EJ633232 |
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| _version_ | 1867181319613579264 |
|---|---|
| author | Chen, Hui-Min Cooper, Michael D. |
| author_facet | Chen, Hui-Min Cooper, Michael D. Chen, Hui-Min Cooper, Michael D. |
| collection | Education Resources Information Center |
| contents | Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System. Chen, Hui-Min Cooper, Michael D. Data Analysis Information Systems Library Catalogs Online Catalogs Online Systems Use Studies Users (Information) Web Based Instruction World Wide Web This study developed an analytical approach to detecting groups with homogenous usage patterns in a Web-based information system. Principal component analysis was used for data reduction, cluster analysis for categorizing usage into groups. The methodology was demonstrated and tested using two independent samples of user sessions from the transaction logs of the University of California's MELVYL[R] online library catalog. (AEF) |
| format | Recurso educativo Open Access |
| id | eric_EJ633232 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 2001 |
| record_format | eric |
| spellingShingle | Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System. Chen, Hui-Min Cooper, Michael D. Data Analysis Information Systems Library Catalogs Online Catalogs Online Systems Use Studies Users (Information) Web Based Instruction World Wide Web Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System. Chen, Hui-Min Cooper, Michael D. Data Analysis Information Systems Library Catalogs Online Catalogs Online Systems Use Studies Users (Information) Web Based Instruction World Wide Web This study developed an analytical approach to detecting groups with homogenous usage patterns in a Web-based information system. Principal component analysis was used for data reduction, cluster analysis for categorizing usage into groups. The methodology was demonstrated and tested using two independent samples of user sessions from the transaction logs of the University of California's MELVYL[R] online library catalog. (AEF) |
| title | Using Clustering Techniques To Detect Usage Patterns in a Web-based Information System. |
| topic | Data Analysis Information Systems Library Catalogs Online Catalogs Online Systems Use Studies Users (Information) Web Based Instruction World Wide Web |
| url | https://eric.ed.gov/?id=EJ633232 |