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Filtering Documents over Time on Evolving Topics - The University of Amsterdam at TREC 2013 KBA CCR
2013
Text Retrieval Conference
In this paper we describe the University of Amsterdam's approach to the TREC 2013 Knowledge Base Acceleration (KBA) Cumulative Citation Recommendation (CCR) track. The task is to filter a stream of documents for documents relevant to a given set of entities. We model the task as a multi-class classification task. Entities may evolve over time and the classifier should be able to adapt to these changes at runtime. To achieve this, the classifier performs online self-learning, i.e., learning only
dblp:conf/trec/Kenter13
fatcat:552epmznwzdtlcavg6qlnmnwyq