Latent Variable Models of Selectional Preference
Latent Variable Models of Selectional Preference
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发表时间：
2010-07
期刊：
影响因子：
1.2
通讯作者：
Diarmuid Ó Séaghdha
中科院分区：
文献类型：
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作者：
Diarmuid Ó Séaghdha
本文描述了所谓的主题模型在选择偏好归纳中的应用。本文提出了三个与潜在狄利克雷分配（Latent Dirichlet Allocation）相关的模型，并在人类合理性判断的数据集上进行了评估。与以前提出的技术相比，这些模型的表现非常有竞争力，特别是对于不频繁的谓词-参数组合，它们在使用相对较少的数据的情况下超过了web规模预测的质量。
This paper describes the application of so-called topic models to selectional preference induction. Three models related to Latent Dirichlet Allocation, a proven method for modelling document-word cooccurrences, are presented and evaluated on datasets of human plausibility judgements. Compared to previously proposed techniques, these models perform very competitively, especially for infrequent predicate-argument combinations where they exceed the quality of Web-scale predictions while using relatively little data.