Document collection visualization and clustering using an atom metaphor for display and interaction
This thesis proposes a new approach to build a 3D clustering visualization system for document clustering by using k-mean algorithm. A cluster will be represented by a neutron (centroid) and electrons (documents) which will keep a distance with neutron by force. Our approach employs quantified domai...
Αποθηκεύτηκε σε:
| Κύριος συγγραφέας: | |
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| Άλλοι συγγραφείς: | |
| Γλώσσα: | eng |
| Έκδοση: |
University of Texas-Pan
2023
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| Διαθέσιμο Online: | https://opac.tvu.edu.vn/pages/opac/wpid-detailbib-id-43011.html |
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| Thư viện lưu trữ: | Trung tâm Học liệu – Phát triển Dạy và Học, Trường Đại học Trà Vinh |
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| Περίληψη: | This thesis proposes a new approach to build a 3D clustering visualization system for document clustering by using k-mean algorithm. A cluster will be represented by a neutron (centroid) and electrons (documents) which will keep a distance with neutron by force. Our approach employs quantified domain knowledge and explorative observation as prediction to map high dimensional data onto 3D space for revealing the relationship among documents. User can perform an intuitive visual assessment of the consistency of the cluster structure. |
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