Case-based Reasoning and Text Mining for Green Building Decision Making
There are great benefits to be obtained by sharing previous experiences in meeting the needs of the standard evaluation systems for green building around the world. To date, there are no existing methods available that enable this to take place in a systematic way. This paper addresses the issue by...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2017
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| Online Access: | http://hdl.handle.net/20.500.11937/55860 |
| _version_ | 1848759726303608832 |
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| author | Xiao, X. Skitmore, M. Hu, Xin |
| author_facet | Xiao, X. Skitmore, M. Hu, Xin |
| author_sort | Xiao, X. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | There are great benefits to be obtained by sharing previous experiences in meeting the needs of the standard evaluation systems for green building around the world. To date, there are no existing methods available that enable this to take place in a systematic way. This paper addresses the issue by developing a green building experience-mining (GBEM) model that enables previous green building solutions to be adapted for a new situation. A database of 10 cases is used to demonstrate and evaluate the effectiveness of the GBEM model. The results confirm the model’s potential to facilitate users in the selection of the solutions when addressing new green building challenges. |
| first_indexed | 2025-11-14T10:04:28Z |
| format | Journal Article |
| id | curtin-20.500.11937-55860 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:04:28Z |
| publishDate | 2017 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-558602018-04-13T04:12:06Z Case-based Reasoning and Text Mining for Green Building Decision Making Xiao, X. Skitmore, M. Hu, Xin There are great benefits to be obtained by sharing previous experiences in meeting the needs of the standard evaluation systems for green building around the world. To date, there are no existing methods available that enable this to take place in a systematic way. This paper addresses the issue by developing a green building experience-mining (GBEM) model that enables previous green building solutions to be adapted for a new situation. A database of 10 cases is used to demonstrate and evaluate the effectiveness of the GBEM model. The results confirm the model’s potential to facilitate users in the selection of the solutions when addressing new green building challenges. 2017 Journal Article http://hdl.handle.net/20.500.11937/55860 10.1016/j.egypro.2017.03.203 http://creativecommons.org/licenses/by-nc-nd/4.0/ Elsevier fulltext |
| spellingShingle | Xiao, X. Skitmore, M. Hu, Xin Case-based Reasoning and Text Mining for Green Building Decision Making |
| title | Case-based Reasoning and Text Mining for Green Building Decision Making |
| title_full | Case-based Reasoning and Text Mining for Green Building Decision Making |
| title_fullStr | Case-based Reasoning and Text Mining for Green Building Decision Making |
| title_full_unstemmed | Case-based Reasoning and Text Mining for Green Building Decision Making |
| title_short | Case-based Reasoning and Text Mining for Green Building Decision Making |
| title_sort | case-based reasoning and text mining for green building decision making |
| url | http://hdl.handle.net/20.500.11937/55860 |