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      Construction of Knowledge Graph English Online Homework Evaluation System Based on Multimodal Neural Network Feature Extraction

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      Computational Intelligence and Neuroscience
      Hindawi

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          Abstract

          This paper defines the data schema of the multimodal knowledge graph, that is, the definition of entity types and relationships between entities. The knowledge point entities are defined as three types of structures, algorithms, and related terms, speech is also defined as one type of entities, and six semantic relationships are defined between entities. This paper adopts a named entity recognition model that combines bidirectional long short-term memory network and convolutional neural network, combines local information and global information of text, uses conditional random field algorithm to label feature sequences, and combines domain dictionary. A knowledge evaluation method based on triplet context information is designed, which combines triplet context information (internal relationship path information in knowledge graph and external text information related to entities in triplet) through knowledge representation learning. The knowledge of triples is evaluated. The knowledge evaluation ability of the English online homework evaluation system was evaluated on the knowledge graph noise detection task, the knowledge graph completion task (entity link prediction task), and the triplet classification task. The experimental results show that the English online homework evaluation system has good noise processing ability and knowledge credibility calculation ability, and has a stronger evaluation ability for low-noise data. Using the online homework platform to implement personalized English homework is conducive to improving students' homework mood, and students' “happy” homework mood has been significantly improved. The implementation of English personalized homework based on the online homework platform is conducive to improving students' homework initiative. With the help of the online homework platform to implement personalized English homework, students' homework time has been reduced, and the homework has been completed well, achieving the purpose of “reducing burden and increasing efficiency.”

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          Information extraction and knowledge graph construction from geoscience literature

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            KnowEdu: A System to Construct Knowledge Graph for Education

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              Knowledge graph based on domain ontology and natural language processing technology for Chinese intangible cultural heritage

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                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                cin
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2022
                13 May 2022
                : 2022
                : 7941414
                Affiliations
                Foreign Languages and International Tourism Department, Chongqing Vocational Institute of Tourism, Chongqing 409000, China
                Author notes

                Academic Editor: Gengxin Sun

                Author information
                https://orcid.org/0000-0002-3497-2962
                Article
                10.1155/2022/7941414
                9122670
                35602643
                fefa28c8-6179-4638-8714-da204850dc7e
                Copyright © 2022 Danlu Liao.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 March 2022
                : 20 April 2022
                : 25 April 2022
                Funding
                Funded by: Chongqing Municipal Education Commission
                Award ID: Z212053
                Award ID: KJQN2020004605
                Funded by: Ministry of Education of the People's Republic of China
                Award ID: WYJZW-2021-105
                Categories
                Research Article

                Neurosciences
                Neurosciences

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