Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchical Text Classification and Evaluation
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Clustering documents in a web directory
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
Automatically collecting, monitoring, and mining japanese weblogs
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Improved annotation of the blogosphere via autotagging and hierarchical clustering
Proceedings of the 15th international conference on World Wide Web
AutoTag: a collaborative approach to automated tag assignment for weblog posts
Proceedings of the 15th international conference on World Wide Web
Enhancing text clustering by leveraging Wikipedia semantics
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Building semantic kernels for text classification using wikipedia
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Cross-Lingual Blog Analysis by Cross-Lingual Comparison of Characteristic Terms and Blog Posts
ISUC '08 Proceedings of the 2008 Second International Symposium on Universal Communication
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Linking topics of news and blogs with wikipedia for complementary navigation
BlogTalk'08/09 Proceedings of the 2008/2009 international conference on Social software: recent trends and developments in social software
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This paper studies the issue of conceptually indexing the blogosphere through the whole hierarchy of Wikipedia entries. This paper proposes how to link Wikipedia entries to blog feeds in the Japanese blogosphere by machine learning, where about 300,000 Wikipedia entries are used for representing a hierarchy of topics. In our experimental evaluation, we achieved over 80% precision in the task.