U3 - mining unordered embedded subtrees using TMG candidate generation
In this paper we present an algorithm for mining of unordered embedded subtrees. This is an importantproblem for association rule mining from semistructured documents, and it has important applications in many biomedical, web and scientific domains. The proposed U3 algorithm is an extension of our g...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
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Institute of Electrical and Electronics Engineers (IEEE) Computer Society
2008
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| Online Access: | http://hdl.handle.net/20.500.11937/44704 |
| _version_ | 1848757078260187136 |
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| author | Hadzic, Fedja Tan, Henry Dillon, Tharam S. |
| author2 | Chengqi Zhang |
| author_facet | Chengqi Zhang Hadzic, Fedja Tan, Henry Dillon, Tharam S. |
| author_sort | Hadzic, Fedja |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In this paper we present an algorithm for mining of unordered embedded subtrees. This is an importantproblem for association rule mining from semistructured documents, and it has important applications in many biomedical, web and scientific domains. The proposed U3 algorithm is an extension of our general tree model guided (TMG) candidate generation framework and it considers both transaction based and occurrence match support. Synthetic and real world data sets are used to experimentally demonstrate the efficiency of our approach to the problem, and the flexibility of our general TMG framework. |
| first_indexed | 2025-11-14T09:22:22Z |
| format | Conference Paper |
| id | curtin-20.500.11937-44704 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:22:22Z |
| publishDate | 2008 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-447042022-12-07T06:50:50Z U3 - mining unordered embedded subtrees using TMG candidate generation Hadzic, Fedja Tan, Henry Dillon, Tharam S. Chengqi Zhang Nick Cercone Lakhmi Jain In this paper we present an algorithm for mining of unordered embedded subtrees. This is an importantproblem for association rule mining from semistructured documents, and it has important applications in many biomedical, web and scientific domains. The proposed U3 algorithm is an extension of our general tree model guided (TMG) candidate generation framework and it considers both transaction based and occurrence match support. Synthetic and real world data sets are used to experimentally demonstrate the efficiency of our approach to the problem, and the flexibility of our general TMG framework. 2008 Conference Paper http://hdl.handle.net/20.500.11937/44704 10.1109/WIIAT.2008.403 Institute of Electrical and Electronics Engineers (IEEE) Computer Society fulltext |
| spellingShingle | Hadzic, Fedja Tan, Henry Dillon, Tharam S. U3 - mining unordered embedded subtrees using TMG candidate generation |
| title | U3 - mining unordered embedded subtrees using TMG candidate generation |
| title_full | U3 - mining unordered embedded subtrees using TMG candidate generation |
| title_fullStr | U3 - mining unordered embedded subtrees using TMG candidate generation |
| title_full_unstemmed | U3 - mining unordered embedded subtrees using TMG candidate generation |
| title_short | U3 - mining unordered embedded subtrees using TMG candidate generation |
| title_sort | u3 - mining unordered embedded subtrees using tmg candidate generation |
| url | http://hdl.handle.net/20.500.11937/44704 |