Dynamic semantic description and search methods for heterogeneous learning resources

• Autorzy: Lai Xiaocong , Pan Ying , Jiang Xueling

Identyfikatory

DOI

10.24425/bpasts.2021.139434

• Języki publikacji: EN

Abstrakty

EN

Learning resources are massive, heterogeneous, and constantly changing. How to find the required resources quickly and accurately has become a very challenging work in the management and sharing of learning resources. According to the characteristics of learning resources, this paper proposes a progressive learning resource description model, which can describe dynamic heterogeneous resource information on a fine-grained level by using information extraction technology, then a semantic annotation algorithm is defined to calculate the semantic of learning resource and add these semantic to the description model. Moreover, a semantic search method is proposed to find the required resources, which calculate the content with the highest similarity to the user query, and then return the results in descending order of similarity. The simulation results show that the method is feasible and effective.

Słowa kluczowe

EN

heterogeneous data; learning resources; semantic description; semantic search

PL

dane niejednorodne; zasoby edukacyjne; opis semantyczny; wyszukiwanie semantyczne

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2022
• Tom: Vol. 70, nr 3
• Strony: art. no. e139434
• Opis fizyczny: Bibliogr. 35 poz., rys., tab.

Twórcy

autor

Lai Xiaocong

• Guangxi Key Lab of Human-machine Interaction and Intelligent Decision, Nanning Normal University, Nanning 530001, People’s Republic of China

autor

Pan Ying

• Guangxi Key Lab of Human-machine Interaction and Intelligent Decision, Nanning Normal University, Nanning 530001, People’s Republic of China

autor

Jiang Xueling

• Guangxi Key Lab of Human-machine Interaction and Intelligent Decision, Nanning Normal University, Nanning 530001, People’s Republic of China

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).