2021 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA) 2021
DOI: 10.1109/aeeca52519.2021.9574313
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An Intelligent Question Answering Method Combining Knowledge Graph and Corpus

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“… [ 110 ] Real-time learning and instructional support multi-modal action fusion module Hybrid Course materials (lecture slides, notes, videos), student learning activity data, discussion forum posts, and DBpedia N/A P, NDCG, F1-score, explainability score •No quantitative figures regarding the size and complexity of the KG, •While the article discusses explainability, it doesn't provide in-depth insights into the explainability methods used. [ 117 ] Semantic Search and QA in the domain of Information Management Systems NER-Bi-LSTM-CRF for Named Entity Recognition and RR-Bi-LSTM-CRF for Relationship Recognition schema-based MIS program at Beijing Jiaotong University N/A F1 Score and mAP (mean Average Precision) •Further improvement is needed in answering recommendations since the system sometimes falls short of user expectations. [ 60 ] QA and course allocation scheduling NLP for entity and relation extraction Schema-based Structural educational information system N/A Case study •Poor assessment methods, •restricted KG resources, •limited scope [ 107 ] QA for unstructured educational text.…”
Section: Applications Of Knowledge Graphs Construction In Educationmentioning
confidence: 99%
“… [ 110 ] Real-time learning and instructional support multi-modal action fusion module Hybrid Course materials (lecture slides, notes, videos), student learning activity data, discussion forum posts, and DBpedia N/A P, NDCG, F1-score, explainability score •No quantitative figures regarding the size and complexity of the KG, •While the article discusses explainability, it doesn't provide in-depth insights into the explainability methods used. [ 117 ] Semantic Search and QA in the domain of Information Management Systems NER-Bi-LSTM-CRF for Named Entity Recognition and RR-Bi-LSTM-CRF for Relationship Recognition schema-based MIS program at Beijing Jiaotong University N/A F1 Score and mAP (mean Average Precision) •Further improvement is needed in answering recommendations since the system sometimes falls short of user expectations. [ 60 ] QA and course allocation scheduling NLP for entity and relation extraction Schema-based Structural educational information system N/A Case study •Poor assessment methods, •restricted KG resources, •limited scope [ 107 ] QA for unstructured educational text.…”
Section: Applications Of Knowledge Graphs Construction In Educationmentioning
confidence: 99%