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MLA

Huang, Weihao, et al. "Structure Graph Refined Information Propagate Network for Aspect-Based Sentiment Analysis." IJDWM vol.19, no.1 2023: pp.1-20. http://doi.org/10.4018/IJDWM.321107

APA

Huang, W., Cai, S., Li, H., & Cai, Q. (2023). Structure Graph Refined Information Propagate Network for Aspect-Based Sentiment Analysis. International Journal of Data Warehousing and Mining (IJDWM), 19(1), 1-20. http://doi.org/10.4018/IJDWM.321107

Chicago

Huang, Weihao, et al. "Structure Graph Refined Information Propagate Network for Aspect-Based Sentiment Analysis," International Journal of Data Warehousing and Mining (IJDWM) 19, no.1: 1-20. http://doi.org/10.4018/IJDWM.321107

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Structure Graph Refined Information Propagate Network for Aspect-Based Sentiment Analysis

International Journal of Data Warehousing and Mining (IJDWM)

The International Journal of Data Warehousing and Mining (IJDWM) a featured IGI Global Core Journal Title, disseminates the latest international research findings in the areas of data management and analyzation. This journal is a forum for state-of-the-art developments, research, and current innovative activities focusing on the integration between the fields of data warehousing and data mining. Featured in prestigious indices including Web of Science® Citation Index Expanded®, Scopus®, Compendex®, INSPEC®, and more, this scholarly journal is led by a leading IGI Global editor and contains research from a growing list of more than 1,500+ industry-leading contributors. This journal is an ideal resource for academic researchers and practicing IT professionals looking for double-blind peer-reviewed articles that provide solutions to ongoing challenges, and new developments within this field.


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