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...

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書誌詳細
第一著者: Nghị Vĩnh Khanh
その他の著者: Dr. Richard H. Fowler, Dr. Wendy A. Lawrence-Fowler, Dr. Zhixiang Chen
言語:eng
出版事項: University of Texas-Pan 2023
オンライン・アクセス: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
その他の書誌記述
要約: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.