A classification scheme of a scientific subject gives an overview of its body of knowledge. It can also be used to facilitate access to research articles and other materials related to the subject. For example, the ACM Computing Classification System (CCS) is used in the ACM Digital Library search interface and also for indexing computer science papers. We observed that a comprehensive classification system like CCS or Mathematics Subject Classification (MSC) does not exist for Computational Linguistics (CL) and Natural Language Processing (NLP). We propose a classification scheme -- CLICKER for CL/NLP based on the analysis of online lectures from 77 university courses on this subject. The currently proposed taxonomy includes 334 topics and focuses on educational aspects of CL/NLP; it is based primarily, but not exclusively, on lecture notes from NLP courses. We discuss how such a taxonomy can help in various real-world applications, including tutoring platforms, resource retrieval, resource recommendation, prerequisite chain learning, and survey generation.
翻译:科学学科的分类办法概括了科学学科的全套知识,还可用于便利查阅与该学科有关的研究文章和其他材料,例如,ACM数字图书馆搜索界面和计算机科学论文索引化使用ACM电子分类系统(CCS),我们注意到,诸如CCS或数学主题分类(MSC)这样的综合分类制度在计算语言和自然语言处理(NLP)方面并不存在。我们根据对77个大学课程的在线讲座的分析,提出了CL/NLP的分类办法 -- -- CLICKER,用于CL/NLP。目前提议的分类方法包括334个专题,重点是CL/NLP的教育方面;它主要但并非完全基于NLP课程的演讲说明。我们讨论了这种分类方法如何帮助各种现实应用,包括辅导平台、资源检索、资源建议、必修链学习和调查生成。