DocumentCode :
1581996
Title :
Semi-automatic building of Domain Module by use of novel machine learning approach
Author :
Deepika, Raj K. ; Saani, H.
Author_Institution :
Dept. of Comput. Sci. & Eng., MEA Eng. Coll., Perinthalmanna, India
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
The Domain Module is considered the core of any TSLSs as it represents the knowledge about a subject matter to be communicated to the learner. In the existing system, proposed a DOM-Sortze is a system that uses natural language processing techniques, heuristic reasoning, and ontologies for the semiautomatic construction of the Domain Module from electronic textbooks. But in this system, still lack in the identification of pedagogical relationships. This is needed to improve in this system. To overcome this issue, Here using learning techniques to learn the new rules in the pedagogical relationships. In this proposed system, proposing the SVM (support vector machine) learning approach intended for learning process. The machine learning methods are used to infer new rules in order to improve the identification of pedagogical relationships or the DRs in the electronic textbooks.
Keywords :
computer aided instruction; electronic publishing; learning (artificial intelligence); support vector machines; DOM-Sortze; SVM learning; TSLS; electronic textbooks; heuristic reasoning; machine learning methods; natural language processing; ontologies; semiautomatic domain module building; support vector machine; technology-supported learning systems; Buildings; Data mining; Databases; Learning systems; Ontologies; Support vector machines; Training; Domain Module; Knowledge acquisition; Ontology; domain engineering; ontology design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
Type :
conf
DOI :
10.1109/ICIIECS.2015.7193195
Filename :
7193195
Link To Document :
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