Rough set model based on the labelled tree
In order to characterize and deal with the vagueness and uncertainty of structured data as well as the compositions and contents implied within semi-structured data models,a labelled tree rough set model（LTRS） was presented by extending the traditional rough set model.Making use of the structure and...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2010-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74648491/ |
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| _version_ | 1841537735749271552 |
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| author | LI Xiong-fei SUN Tao GUO Jian-fang |
| author_facet | LI Xiong-fei SUN Tao GUO Jian-fang |
| author_sort | LI Xiong-fei |
| collection | DOAJ |
| description | In order to characterize and deal with the vagueness and uncertainty of structured data as well as the compositions and contents implied within semi-structured data models,a labelled tree rough set model（LTRS） was presented by extending the traditional rough set model.Making use of the structure and content of the labelled tree,the basic concepts of rough set were redefined,such as equivalence relation,indiscernibility relation,upper approximation and lower approximation,etc.Furthermore,the discernibility matrix and decision rules were described.Using the labeled tree constructed by XML case questionary of epidemic encephalitis B from some area as an example,the extraction method of decision rules was presented based on the definitions given above.The decision rules produced by LTRS can be used to guide the clinic classification in the case of epidemic encephalitis B. |
| format | Article |
| id | doaj-art-7f209deecc354f0eb692cca2cd6df304 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2010-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-7f209deecc354f0eb692cca2cd6df3042025-01-14T08:25:23ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2010-01-0131354374648491Rough set model based on the labelled treeLI Xiong-feiSUN TaoGUO Jian-fangIn order to characterize and deal with the vagueness and uncertainty of structured data as well as the compositions and contents implied within semi-structured data models,a labelled tree rough set model（LTRS） was presented by extending the traditional rough set model.Making use of the structure and content of the labelled tree,the basic concepts of rough set were redefined,such as equivalence relation,indiscernibility relation,upper approximation and lower approximation,etc.Furthermore,the discernibility matrix and decision rules were described.Using the labeled tree constructed by XML case questionary of epidemic encephalitis B from some area as an example,the extraction method of decision rules was presented based on the definitions given above.The decision rules produced by LTRS can be used to guide the clinic classification in the case of epidemic encephalitis B.http://www.joconline.com.cn/zh/article/74648491/rough setlabelled treeXMLdecision rules |
| spellingShingle | LI Xiong-fei SUN Tao GUO Jian-fang Rough set model based on the labelled tree Tongxin xuebao rough set labelled tree XML decision rules |
| title | Rough set model based on the labelled tree |
| title_full | Rough set model based on the labelled tree |
| title_fullStr | Rough set model based on the labelled tree |
| title_full_unstemmed | Rough set model based on the labelled tree |
| title_short | Rough set model based on the labelled tree |
| title_sort | rough set model based on the labelled tree |
| topic | rough set labelled tree XML decision rules |
| url | http://www.joconline.com.cn/zh/article/74648491/ |
| work_keys_str_mv | AT lixiongfei roughsetmodelbasedonthelabelledtree AT suntao roughsetmodelbasedonthelabelledtree AT guojianfang roughsetmodelbasedonthelabelledtree |