BriefGPT.xyz
Apr, 2017
有监督的方面提取的终身学习CRF
Lifelong Learning CRF for Supervised Aspect Extraction
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Lei Shu, Hu Xu, Bing Liu
TL;DR
本文介绍了有监督的方面提取，展示了如果系统从许多过去的领域中进行方面提取并将结果作为知识保留下来，条件随机场可以以终身学习的方式利用这些知识，在新的领域中提取的效果明显优于传统的不使用先前知识的条件随机场。关键创新在于即使在 CRF 训练之后，模型仍然可以通过其应用中的经验来改进提取。
Abstract
This paper makes a focused contribution to
supervised aspect extraction
. It shows that if the system has performed aspect extraction from many past domains and retained their results as knowledge,
conditional random fie
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