Title :
A Vector Space Model Based Education Resources Automatic Classifier
Author_Institution :
Sch. of Comput. & Inf., Shanghai Second Polytech. Univ., Shanghai, China
Abstract :
Along with the rapid improvements of informational technology, educational data grows quickly. Such data become massive and raw data. Researchers develop educational standards to regular such data. However, the standards are multiple and the education resources based on different education standards have different structure, which is hard to be shared. Most of them have become Information Islands and prevent education resources from being built collaboratively or utilized. Furthermore, it is also difficult to integrate the current education resources by Human and material resources. Therefore, it is necessary to leverage Natural Language Processing Technologies to categorize education resources automatically by computers. This paper research on the specificity of education resources categorization, introduce Vector Space Model technologies in it and put forward a method for Vector Space Model based Education Resources Automatic Classifier.
Keywords :
educational administrative data processing; pattern classification; text analysis; education resources automatic classifier; education resources categorization; natural language processing technologies; vector space model; Computational modeling; Computers; Standards; Support vector machine classification; Training; Vectors; Education Resources; Natural Language Processing; Text Classification; Vector Space Model;
Conference_Titel :
Enterprise Systems Conference (ES), 2014
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-5553-4