Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Expertise recommender: a flexible recommendation system and architecture
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Expertise identification using email communications
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Searching for expertise in social networks: a simulation of potential strategies
GROUP '05 Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work
Deriving wishlists from blogs show us your blog, and we'll tell you what books to buy
Proceedings of the 15th international conference on World Wide Web
Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
Automatic Identification of Chinese Weblogger's Interests Based on Text Classification
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Detection of Bloggers' Interests: Using Textual, Temporal, and Interactive Features
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Trend detection in folksonomies
SAMT'06 Proceedings of the First international conference on Semantic and Digital Media Technologies
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
ExpertiseNet: relational and evolutionary expert modeling
UM'05 Proceedings of the 10th international conference on User Modeling
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The architecture of participation and sharing that encourage users to add value is one of the fundamental characteristics of a successful Web 2.0 application. Blog, as a personal publish platform on the web, removes the intermediation for channel selection thus everyone can represent himself/herself without any filtering mechanism. In this research, we present a methodology to derive user's degree of expertise from blog data and conduct an experiment using data collected from a enterprise blog system. The result shows that the average precision reaches around 0.8 and which factor is useful in our proposed method.