Indexing student essays paragraphs using LSA over an integrated ontological space

eLearn '04: Proceedings of the Workshop on eLearning for Computational Linguistics and Computational Linguistics for eLearning(2004)

引用 3|浏览7
暂无评分
摘要
A full understanding of text is out of reach of current human language technology. However, a shallow Natural Language Processing (NLP) approach can be used to provide automated help in the evaluation of essays. The main idea of this paper is that Latent Semantic Indexing (LSA) can be used in conjunction with ontologies and First order Logic (FOL) to locate segments relevant to a question in a student essay. Our test bed, in a first instance, is a set of ontologies such the AKT reference ontology (describing academic life), Newspaper and a Koala ontology (concerning koalas' habitat).
更多
查看译文
关键词
AKT reference ontology,Koala ontology,First order Logic,Latent Semantic Indexing,academic life,automated help,current human language technology,full understanding,main idea,shallow Natural Language Processing,Indexing student essay,integrated ontological space
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要