ISTI at TREC Microblog Track 2012: Real-Time Filtering Through Supervised Learning
CONSIGLIO NAZIONALE DELLE RICHERCHE PISA (ITALY)
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Our approach to the microblog filtering task is based on learning a relevance classifier from an initial training set of relevant and non relevant tweets, generated by using a simple retrieval method. The classifier is then retrained using the simulated user feedback collected during the training process, in order to improve its accuracy as the filtering process goes on. In the official runs the system scored low effectiveness values suffering a strong imbalance toward recall.
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