论文标题
Autonlp：NLP功能建议应用程序建议
autoNLP: NLP Feature Recommendations for Text Analytics Applications
论文作者
论文摘要
在设计基于机器学习的文本分析应用程序时，NLP数据科学家通常会根据其知识和相关问题的经验手动确定使用哪些NLP功能。这导致在功能工程过程中的努力增加，并使跨语义相关应用程序的功能自动重复使用本质上困难。在本文中，我们通过概述语言的结构来指定NLP功能的结构，并提出了一种跨应用程序的重复使用方法，以增加识别最佳功能的可能性，并提出了一种方法。
While designing machine learning based text analytics applications, often, NLP data scientists manually determine which NLP features to use based upon their knowledge and experience with related problems. This results in increased efforts during feature engineering process and renders automated reuse of features across semantically related applications inherently difficult. In this paper, we argue for standardization in feature specification by outlining structure of a language for specifying NLP features and present an approach for their reuse across applications to increase likelihood of identifying optimal features.
