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Please use this identifier to cite or link to this item: http://ir.lib.stu.edu.tw:80/ir/handle/310903100/1336

Title: 基於Tag分析之相似瀏覽興趣Blogger研究
The study of using Tag Analysis to Group Bloggers with the Similar Browsing Interest
Authors: 張孟秀
Meng-Hsiu Chang
Contributors: Yi-Jen Su
資訊工程系碩士班
Keywords: Folksonomy;Tag;Social Network Analysis
Folksonomy;Tag;Social Network Analysis
Date: 2009
Issue Date: 2011-05-24 15:28:50 (UTC+8)
Publisher: 高雄市:[樹德科技大學資訊工程系碩士班]
Abstract: 自Web 2.0推出後,其相關技術與服務已普遍建置於各入口網站及社群網站上,其中又以部落格(Blog)服務最廣受到網路族的青睞。面對資訊超載的網際網路,部落客(Blogger)需要一套有效地分類與管理各類媒體(文章、照片及影片)的機制,通常以使用Tag來輔助分類的方法最為普遍。如何將具有相似興趣的部落客之Tag聚集起來,形成一個具有高品質的結合眾人分類共識的「Folksonomy」就成為一個有趣的議題。本研究提出以每一位部落客所使用的Tag Cloud作為個人興趣判斷的依據,然後使用Social Network Analysis (SNA)中的社群發現(Community Discovery)技術去辨識具有相似興趣的部落客,並以著名的書籤分享網站「Del.icio.us」作為本研究的實驗資料來源。
Web 2.0 technologies and services have been widely deployed in various portals and network-community websites. Of all these services, the Blog has attracted the most users. In the age of information overload, bloggers need an efficient and effective classification method to manage various types of media (e.g. articles, photos and films). Generally, tagging is the most favored sorting method. How to collect tags set by bloggers of the same interests to form a high-quality “Folksonomy” thus becomes an important issue. This paper proposes to identify the interests of a blogger by his/her Tag Cloud. Then Community Discovery, a social network analysis method, could be employed to group bloggers of the same interests. The dataset in this experiment comes from the famous bookmark-sharing website “Del.icio.us”.
Appears in Collections:[資訊工程系(所) ] 博碩士論文

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