%A Hao Wu
%A Guang Qiu
%A Xiaofei He
%A Yuan Shi
%A Mingcheng Qu
%A Jing Shen
%A Jiajun Bu
%A Chun Chen
%T Advertising Keyword Generation Using Active Learning
%X This paper proposes an efficient relevance feedback based interactive model for keyword generation in sponsored search advertising. We formulate the ranking of relevant terms as a supervised learning problem and suggest new terms for the seed by leveraging user relevance feedback information. Active learning is employed to select the most informative samples from a set of candidate terms for user labeling. Experiments show our approach improves the relevance of generated terms signi?cantly with little user effort required. 
%C Madrid, Spain
%D 2009
%P 1095-1095
%L www2009128

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