document: Advertising keyword generation using active learning 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 significantly with little user effort required .
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