A structure preserving flat data format representation for tree-structured data
Mining of semi-structured data such as XML is a popular research topic due to many useful applications. The initial work focused mainly on values associated with tags, while most of recent developments focus on discovering association rules among tree structured data objects to preserve the structur...
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| Format: | Conference Paper |
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Springer
2012
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| Online Access: | http://conferences.telecom-bretagne.eu/data/qimie2011/hadzic-informal_QIMIE_2011.pdf http://hdl.handle.net/20.500.11937/37719 |
| _version_ | 1848755125613494272 |
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| author | Hadzic, Fedja |
| author2 | L. Cao |
| author_facet | L. Cao Hadzic, Fedja |
| author_sort | Hadzic, Fedja |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Mining of semi-structured data such as XML is a popular research topic due to many useful applications. The initial work focused mainly on values associated with tags, while most of recent developments focus on discovering association rules among tree structured data objects to preserve the structural information. Other data mining techniques have had limited use in tree-structured data analysis as they were mainly designed to process flat data format with no need to capture the structural properties of data objects. This paper proposes a novel structure-preserving way for representing tree-structured document instances as records in a standard flat data structure to enable applicability of a wider range of data analysis techniques. The experiments using synthetic and real world data demonstrate the effectiveness of the proposed approach. |
| first_indexed | 2025-11-14T08:51:20Z |
| format | Conference Paper |
| id | curtin-20.500.11937-37719 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T08:51:20Z |
| publishDate | 2012 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-377192023-02-07T08:01:20Z A structure preserving flat data format representation for tree-structured data Hadzic, Fedja L. Cao J. Huang J. Bailey Y. Koh J. Luo XML mining decision tree learning from XML data tree mining Mining of semi-structured data such as XML is a popular research topic due to many useful applications. The initial work focused mainly on values associated with tags, while most of recent developments focus on discovering association rules among tree structured data objects to preserve the structural information. Other data mining techniques have had limited use in tree-structured data analysis as they were mainly designed to process flat data format with no need to capture the structural properties of data objects. This paper proposes a novel structure-preserving way for representing tree-structured document instances as records in a standard flat data structure to enable applicability of a wider range of data analysis techniques. The experiments using synthetic and real world data demonstrate the effectiveness of the proposed approach. 2012 Conference Paper http://hdl.handle.net/20.500.11937/37719 http://conferences.telecom-bretagne.eu/data/qimie2011/hadzic-informal_QIMIE_2011.pdf Springer restricted |
| spellingShingle | XML mining decision tree learning from XML data tree mining Hadzic, Fedja A structure preserving flat data format representation for tree-structured data |
| title | A structure preserving flat data format representation for tree-structured data |
| title_full | A structure preserving flat data format representation for tree-structured data |
| title_fullStr | A structure preserving flat data format representation for tree-structured data |
| title_full_unstemmed | A structure preserving flat data format representation for tree-structured data |
| title_short | A structure preserving flat data format representation for tree-structured data |
| title_sort | structure preserving flat data format representation for tree-structured data |
| topic | XML mining decision tree learning from XML data tree mining |
| url | http://conferences.telecom-bretagne.eu/data/qimie2011/hadzic-informal_QIMIE_2011.pdf http://hdl.handle.net/20.500.11937/37719 |