The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
BlogRank: ranking weblogs based on connectivity and similarity features
AAA-IDEA '06 Proceedings of the 2nd international workshop on Advanced architectures and algorithms for internet delivery and applications
Description and Prediction of Slashdot Activity
LA-WEB '07 Proceedings of the 2007 Latin American Web Conference
B2Rank: An Algorithm for Ranking Blogs Based on Behavioral Features
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Analyzing reading behavior by blog mining
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
An analysis of network structure and post content for blog post recommendation
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications
Slovak Blog Clustering Enhanced by Mining the Web Comments
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
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In this paper, we analyze people’s reading and commenting behaviors in blogspace and proposed an algorithm for blog ranking. Upon two selected communities, AI and Medical, we show how comments, reading records, active browsing and multi time browsing can help to construct the weblog graph and reflect a blog’s popularity. Based on these analysis, we propose cRank, a graph based algorithm, to rank blog among community members. Finally, we divide our dataset temporally and present how the proposed algorithm can make prediction on blogs’ rankings. The experiment shows that cRank has a better performance upon several baseline systems.