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A topic modeling‐based bibliometric exploration of automatic summarization research
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1 of the 195 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1155/2022/1166989 (notice 2023-08-23).
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/widm.1517openalex-snapshotThe state‐of‐art review of ultra‐precision machining using text mining: Identification of main themes and recommendations for the future direction
inferredcites →https://doi.org/10.1002/widm.1526openalex-snapshotThe role of lifelong machine learning in bridging the gap between human and machine learning: A scientometric analysis
inferredcites →https://doi.org/10.1007/s11227-021-03950-xopenalex-snapshotImproving the readability and saliency of abstractive text summarization using combination of deep neural networks equipped with auxiliary attention mechanism
inferredcites →https://doi.org/10.1016/j.caeai.2020.100005openalex-snapshotA multi-perspective study on Artificial Intelligence in Education: grants, conferences, journals, software tools, institutions, and researchers
inferredcites →https://doi.org/10.1016/j.compedu.2020.103855openalex-snapshotDetecting latent topics and trends in educational technologies over four decades using structural topic modeling: A retrospective of all volumes of Computers & Education
inferredcites →https://doi.org/10.1016/j.eswa.2022.119308openalex-snapshotSGCSumm: An extractive multi-document summarization method based on pre-trained language model, submodularity, and graph convolutional neural networks
inferredcites →https://doi.org/10.1016/j.eswa.2023.120302openalex-snapshotEnhanced sentence representation for extractive text summarization: Investigating the syntactic and semantic features and their contribution to sentence scoring
inferredcites →https://doi.org/10.1016/j.ipm.2023.103291openalex-snapshotAn extract-then-abstract based method to generate disaster-news headlines using a DNN extractor followed by a transformer abstractor
inferredcites →https://doi.org/10.1016/j.jbi.2023.104358openalex-snapshotDischarge summary hospital course summarisation of in patient Electronic Health Record text with clinical concept guided deep pre-trained Transformer models
inferredcites →https://doi.org/10.1016/j.respol.2018.04.012openalex-snapshotThe evolution of government sponsored collaboration network and its impact on innovation: A bibliometric analysis in the Chinese solar PV sector
inferredcites →https://doi.org/10.1145/3265751openalex-snapshotPause-Based Phrase Extraction and Effective OOV Handling for Low-Resource Machine Translation Systems
inferredcites →https://doi.org/10.1145/3617680openalex-snapshotA Survey of Controllable Text Generation Using Transformer-based Pre-trained Language Models
inferredcites →https://doi.org/10.1155/2022/1166989openalex-snapshot[Retracted] Automatic Text Summarization for Public Health WeChat Official Accounts Platform Base on Improved TextRank
inferredcites →https://doi.org/10.18653/v1/d18-1206openalex-snapshotDon’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
inferredcites →https://doi.org/10.3390/app112210596openalex-snapshotEvent Monitoring and Intelligence Gathering Using Twitter Based Real-Time Event Summarization and Pre-Trained Model Techniques
What points at this work
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inferred← citeshttps://doi.org/10.3390/app142311462openalex-snapshotCharting the Growth of Text Summarisation: A Data-Driven Exploration of Research Trends and Technological Advancements
inferred← citeshttps://doi.org/10.3390/w17202994openalex-snapshotA Bibliometric-Systematic Literature Review (B-SLR) of Machine Learning-Based Water Quality Prediction: Trends, Gaps, and Future Directions
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