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Hierarchical multi-label classification of social text streams
2014
Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval - SIGIR '14
Hierarchical multi-label classification assigns a document to multiple hierarchical classes. In this paper we focus on hierarchical multi-label classification of social text streams. Concept drift, complicated relations among classes, and the limited length of documents in social text streams make this a challenging problem. Our approach includes three core ingredients: short document expansion, time-aware topic tracking, and chunk-based structural learning. We extend each short document in
doi:10.1145/2600428.2609595
dblp:conf/sigir/RenPLDR14
fatcat:4h5pyvebgrdu7h4h7rnbnjxfpe