Abstract
Active stream learning is frequently used to acquire labelsfor instances and less frequently to determine which features should beconsidered as the stream evolves. We introduce a framework for activefeature selection, intended to adapt the feature space of a polarity learnerover a stream of opinionated documents. We report on the first results ofour framework on substreams of reviews on different product categories.
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