Please use this identifier to cite or link to this item: https://doi.org/10.1145/1552291.1552292
DC FieldValue
dc.titleAn online blog reading system by topic clustering and personalized ranking
dc.contributor.authorLi, X.
dc.contributor.authorYan, J.
dc.contributor.authorFan, W.
dc.contributor.authorLiu, N.
dc.contributor.authorYan, S.
dc.contributor.authorChen, Z.
dc.date.accessioned2014-06-17T02:38:33Z
dc.date.available2014-06-17T02:38:33Z
dc.date.issued2009-07-01
dc.identifier.citationLi, X., Yan, J., Fan, W., Liu, N., Yan, S., Chen, Z. (2009-07-01). An online blog reading system by topic clustering and personalized ranking. ACM Transactions on Internet Technology 9 (3) : -. ScholarBank@NUS Repository. https://doi.org/10.1145/1552291.1552292
dc.identifier.issn15335399
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/55047
dc.description.abstractThere is an increasing number of people reading, writing, and commenting on blogs. According to a recent survey made by Technorati, there are about 75,000 new blogs and 1.2 million new posts everyday. However, it is difficult and time consuming for a blog reader to find the most interesting posts in the huge and dynamic blog world. In this article, an online Personalized Blog Reader (PBR) system is proposed, which facilitates blog readers in browsing the coolest and newest blog posts of their interests by automatically clustering the most relevant stories. PBR aims to make a user's potential favorite topics always ranked higher than those nonfavorite ones. This is accomplished in the following steps. First, the system collects and provides a unified incremental index of posts coming from different blogs. Then, an incremental clustering algorithm with a flexible half-bounded window of observation is proposed to satisfy the requirements of online processing. It learns people's personalized reading preferences to present a user with a final reading list. The experimental results show that the proposed incremental clustering algorithm is effective and efficient, and the personalization of the PBR performs well.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1552291.1552292
dc.sourceScopus
dc.subjectBlog
dc.subjectConnected subgraph
dc.subjectContent information
dc.subjectLink information
dc.subjectPersonalization
dc.subjectRanking
dc.subjectStory
dc.subjectTopic
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1145/1552291.1552292
dc.description.sourcetitleACM Transactions on Internet Technology
dc.description.volume9
dc.description.issue3
dc.description.page-
dc.identifier.isiut000268966100001
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

10
checked on Aug 22, 2019

WEB OF SCIENCETM
Citations

6
checked on Aug 13, 2019

Page view(s)

64
checked on Aug 18, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.