Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation

empirical methods in natural language processing, pp. 2588-2597, 2017.

Cited by: 14|Bibtex|Views90|DOI:https://doi.org/10.18653/v1/d17-1275
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

One weakness of machine-learned NLP models is that they typically perform poorly on out-of-domain data. In this work, we study the task of identifying products being bought and sold in online cybercrime forums, which exhibits particularly challenging cross-domain effects. We formulate a task that represents a hybrid of slot-filling inform...More

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