Application of the LDA Model to Semantic Annotation of Web-based English Educational Resources
Keywords:LDA model; Web English; Educational resources; Semantic annotation
Based on the LDA model, this paper builds a three-layer semantic model of Web English educational resources “document-topic-keyword”, models the semantic topics of resource documents, and obtains the semantic topics and keywords of document resources as the semantic labels of resources. The experimental results show that document LDA topic modeling is beneficial to the macroscopic classification of Web English educational resources. The experimental results show that LDA topic modeling of documents is useful for macroscopic cataloging of Web English educational resources, highlighting teaching priorities, difficulties, and interrelationships, while LDA modeling of teaching topics with the same teaching content expands the metadata generation method of resource description based on the basic education metadata standard and provides more information about the inherent characteristics of resources. The semantic information can be used to mine the semantic thematic features and detailed differences inherent in the resources, and the final performance analysis verifies the parallel computing advantages of the LDA model in a big data environment.
Goodman M G, Alvarez M, Halstead S B. Secondary infection as a risk factor for dengue hemorrhagic fever/dengue shock syndrome: a historical perspective and role of antibody-dependent enhancement of infection[J]. Archives of virology, 2013, 158(7): 1445–1459.
Jackson P, Raiji M T. Evaluation and Mangement of Intestinal Obstruction[J]. American family physician, 2011, 83(2): 159–165.
Vidal J C, Lama M, Otero-García E, et al. Graph-based semantic annotation for enriching educational content with linked data[J]. Knowledge-Based Systems, 2014, 55: 29–42.
Xu H, Zhang R, Lin C, et al. Novel approach of semantic annotation by fuzzy ontology based on variable precision rough set and concept lattice[J]. Int. J. Hybrid Inf. Technol, 2016, 9(4): 25–40.
Kadda B, Ahmed L. Semantic annotation of pedagogic documents[J]. International Journal of Modern Education and Computer Science, 2016, 8(6): 13.
Vrablecová P, Šimko M. Supporting semantic annotation of educational content by automatic extraction of hierarchical domain relationships[J]. IEEE transactions on learning technologies, 2016, 9(3): 285–298.
Koutsomitropoulos D A, Solomou G D. A learning object ontology repository to support annotation and discovery of educational resources using semantic thesauri[J]. IFLA journal, 2018, 44(1): 4–22.
Jensen J. A systematic literature review of the use of semantic web technologies in formal education[J]. British Journal of Educational Technology, 2019, 50(2): 505–517.
Sánchez-Nielsen E, Chávez-Gutiérrez F, Lorenzo-Navarro J. A semantic parliamentary multimedia approach for retrieval of video clips with content understanding[J]. Multimedia Systems, 2019, 25(4): 337–354.
Balavivekanandhan A. A technique for semantic annotation and retrieval of e-learning objects[J]. International Journal of Business Intelligence and Data Mining, 2020, 17(1): 12–31.
Zarzour H, Sellami M. A linked data-based collaborative annotation system for increasing learning achievements[J]. Educational Technology Research and Development, 2017, 65(2): 381–397.
Chi Y, Qin Y, Song R, et al. Knowledge graph in smart education: A case study of entrepreneurship scientific publication management[J]. Sustainability, 2018, 10(4): 995.
Stepanov E A, Chowdhury S A, Bayer A O, et al. Cross-language transfer of semantic annotation via targeted crowdsourcing: task design and evaluation[J]. Language Resources and Evaluation, 2018, 52(1): 341–364.
Simko M, Bielikova M. Lightweight domain modeling for adaptive web-based educational system[J]. Journal of Intelligent Information Systems, 2019, 52(1): 165–190.
Neal M L, König M, Nickerson D, et al. Harmonizing semantic annotations for computational models in biology[J]. Briefings in bioinformatics, 2019, 20(2): 540–550.
Wongthongtham P, Chan K Y, Potdar V, et al. State-of-the-art ontology annotation for personalised teaching and learning and prospects for smart learning recommender based on multiple intelligence and fuzzy ontology[J]. International Journal of Fuzzy Systems, 2018, 20(4): 1357–1372.
Zarzour H, Sellami M. Effects of a linked data-based annotation approach on students’ learning achievement and cognitive load[J]. Interactive Learning Environments, 2018, 26(8): 1090–1099.
Gayoso-Cabada J, Goicoechea-de-Jorge M, Gómez-Albarrán M, et al. Ontology-Enhanced Educational Annotation Activities[J]. Sustainability, 2019, 11(16): 4455.
Gomes Jr J, Dias L L, Soares E R, et al. Framework for Knowledge Discovery in Educational Video Repositories[J]. Computing and Informatics, 2020, 38(6): 1375–1402.
Al-Osta M, Ahmed B, Abdelouahed G. A lightweight semantic web-based approach for data annotation on IoT gateways[J]. Procedia computer science, 2017, 113(1): 186–193.
Rezgui K, Mhiri H. Towards a Semantic Framework for Lifelong Integrated Competency Management and Development[J]. The Computer Journal, 2020, 63(7): 1004–1016.
Yanchinda J, Yodmongkol P, Chakpitak N. Measurement of Learning Process by Semantic Annotation Technique on Bloom’s Taxonomy Vocabulary[J]. International Education Studies, 2016, 9(1): 107–122.
Pereira C K, Siqueira S W M, Nunes B P, et al. Linked data in Education: a survey and a synthesis of actual research and future challenges[J]. IEEE Transactions on Learning Technologies, 2017, 11(3): 400–412.