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dc.contributor.authorKuan, Yen-Tingen_US
dc.contributor.authorTai, Ming-Hungen_US
dc.contributor.authorKuan, Hsuan-Haoen_US
dc.contributor.authorHo, Tan-Chien_US
dc.contributor.authorWang, Yu-Shuenen_US
dc.contributor.authorLin, Wen-Chiehen_US
dc.contributor.authorChuang, Jung-Hongen_US
dc.date.accessioned2017-04-21T06:49:26Z-
dc.date.available2017-04-21T06:49:26Z-
dc.date.issued2015en_US
dc.identifier.isbn978-1-4673-7343-2en_US
dc.identifier.urihttp://hdl.handle.net/11536/135798-
dc.description.abstractWeb media is becoming popular nowadays for people to read news or articles. It is interesting and important for the web media providers to learn the browsing behaviors of their readers and authors. In this paper, we present a visual analytics system for discovering the browsing and authoring behaviors in web media based on users web page clickstream data. Our system provides multiple views of visualization with user interaction, including a scatter plot providing an overview to help analysts locate data of interest, and a force-directed graph for investigating relations between data entities. Interesting behaviors have been explored and found by using the proposed multiple views system.en_US
dc.language.isoen_USen_US
dc.titleInteractive Visual Analysis of Browsing and Authoring Behaviors in Web Mediaen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2015 BIG DATA VISUAL ANALYTICS (BDVA)en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000380399900015en_US
dc.citation.woscount0en_US
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