Infobright for analyzing social sciences data
There are considerable challenges in analyzing, interpreting, and reporting word-based social sciences data. Infobright data warehousing technology was used to analyze a typical data set from the social sciences. Infobright was found to require augmentation for analyzing qualitative data provided as...
| Main Authors: | , |
|---|---|
| Format: | Conference Paper |
| Published: |
2009
|
| Online Access: | http://hdl.handle.net/20.500.11937/25260 |
| _version_ | 1848751658941546496 |
|---|---|
| author | Johnson, J. Johnson, Genevieve |
| author_facet | Johnson, J. Johnson, Genevieve |
| author_sort | Johnson, J. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | There are considerable challenges in analyzing, interpreting, and reporting word-based social sciences data. Infobright data warehousing technology was used to analyze a typical data set from the social sciences. Infobright was found to require augmentation for analyzing qualitative data provided as short stories by human subjects. A requirements specification for mining data that are subject to interpretation is proposed and left to the Infobright designers to implement should they so choose. Infobright was chosen as a system for implementing the data set because its rough set based intelligence appears to be extensible with moderate effort to implement the data warehousing requirements of word based data. © 2009 Springer-Verlag Berlin Heidelberg. |
| first_indexed | 2025-11-14T07:56:14Z |
| format | Conference Paper |
| id | curtin-20.500.11937-25260 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:56:14Z |
| publishDate | 2009 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-252602017-09-13T15:21:24Z Infobright for analyzing social sciences data Johnson, J. Johnson, Genevieve There are considerable challenges in analyzing, interpreting, and reporting word-based social sciences data. Infobright data warehousing technology was used to analyze a typical data set from the social sciences. Infobright was found to require augmentation for analyzing qualitative data provided as short stories by human subjects. A requirements specification for mining data that are subject to interpretation is proposed and left to the Infobright designers to implement should they so choose. Infobright was chosen as a system for implementing the data set because its rough set based intelligence appears to be extensible with moderate effort to implement the data warehousing requirements of word based data. © 2009 Springer-Verlag Berlin Heidelberg. 2009 Conference Paper http://hdl.handle.net/20.500.11937/25260 10.1007/978-3-642-10583-8_12 restricted |
| spellingShingle | Johnson, J. Johnson, Genevieve Infobright for analyzing social sciences data |
| title | Infobright for analyzing social sciences data |
| title_full | Infobright for analyzing social sciences data |
| title_fullStr | Infobright for analyzing social sciences data |
| title_full_unstemmed | Infobright for analyzing social sciences data |
| title_short | Infobright for analyzing social sciences data |
| title_sort | infobright for analyzing social sciences data |
| url | http://hdl.handle.net/20.500.11937/25260 |