Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Deriving a large scale taxonomy from Wikipedia
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Are semantically related links more effective for retrieval?
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Proceedings of the 4th Information Interaction in Context Symposium
Extracting semantic knowledge from Wikipedia category names
Proceedings of the 2013 workshop on Automated knowledge base construction
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Wikipedia's rich category structure has helped make it one of the largest semantic taxonomies in existence, a property that has been central to much recent research. However, Wikipedia's category representation is simplistic: an article contains a single list of categories, with no data about their relative importance. We investigate the ordering of category lists to determine how a category's position in the list correlates with its relevance to the article and overall significance. We identify a number of interesting connections between a category's position and its persistence within the article, age, popularity, size, and descriptiveness.