Title :
Keyword extraction for mining meaningful learning-contents on the Web using Wikipedia
Author :
Toyota, Tetsuya ; Yuan Sun
Author_Institution :
Res. Organ. of Inf. & Syst., Nat. Inst. of Inf., Tokyo, Japan
Abstract :
The purpose of this paper is to provide a solution of extracting appropriate keywords to identify meaningful learning-contents on the Web. There are some issues in identifying documents that have learning content. Firstly, the documents need to be identified according to the learning area of a student´s school year. Secondly, the documents need to be identified according to the learning area that the student is now studying or studied. In this paper, we present a method of extracting keywords for mining meaningful learning-contents using Wikipedia. At first, we select the articles in Wikipedia with the arbitrary input keyword of learning items. Then, we select other Wikipedia´s articles related to the articles selected by the first process, using links and categories of Wikipedia. Furthermore, we calculate degrees of association between the articles and the keywords using PF-IBF, and put the degree on each keyword. Finally, we screen the keywords using his/her curriculum guideline to adjust the keywords to the learning area of the student´s school year. In the next step, we are planning to develop a method of screening keywords according to each student´s ability, so that we can select more appropriate keywords for each student.
Keywords :
Internet; Web sites; computer aided instruction; data mining; document handling; PF-IBF; Wikipedia; World Wide Web; appropriate keyword extraction; curriculum guideline; document identification; meaningful learning-content mining; Data mining; Educational institutions; Electronic publishing; Encyclopedias; Equations; Internet; Wikipedia; e-learning; educational technology;
Conference_Titel :
Frontiers in Education Conference (FIE), 2014 IEEE
DOI :
10.1109/FIE.2014.7044344