利用大眾分類法改善部落格排名效能; Using Folksonomy to Improve the Performance of Blog Ranking

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Computer Science and Information Engineering > Electronic Thesis & Dissertation > Item 987654321/9693

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/9693

Title:	利用大眾分類法改善部落格排名效能;Using Folksonomy to Improve the Performance of Blog Ranking
Authors:	范嘉仁;Jia-Zen Fan
Contributors:	資訊工程研究所
Keywords:	大眾分類;部落格;網頁排名;Blog;PageRank;Folksonomy
Date:	2008-07-09
Issue Date:	2009-09-22 11:53:44 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	使用PageRank作為排序網路搜尋結果已被採信為一種可靠的方法，然而，其結果並不是讓人那麼滿意。許多研究發現部落格文章之間的相互連結之少，使得PageRank無法將新奇又相關性高但較少被連結的部落格文章推薦給搜尋者。再者，PageRank缺乏主題性的探索，這使得排名結果雖然有利於最有價值的部落格文章，但不一定利於最相關主題的部落格文章。本篇文章嘗試就這些缺點提出更好的排序方法。更進一步，我們比較現有的主題性網頁排名方法和大眾分類法(Folksonomy)做為主題分類的依據時的可靠程度，我們發現Folksonomy的結果較能符合搜尋者的期待。這篇論文將描述這個發現。 Using PageRank to ranking search results on the web has been adopted as a reliable method; however, the results are not so satisfying. Many researches found that there are too few interlinks between blogposts that PageRank will be unable to recommended novel and high-related blogposts weak-connected to the users. Moreover, PageRank is lack of Topic discovery, which makes the rank advantages the valuable blogposts but does nothing to the relative blogposts. We attempted to present a better ranking method on solving these problem. Moreover, we tried to compare the degree of reliably between the latest topic-discovery page ranking method and Folksonomy as they are both used to generate the common topic relation. This paper will describe this discovery.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

Files in This Item:

File	Size	Format

社群 sharing

Loading...