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Method and Dataset Mining in Scientific Papers
- Source :
- IEEE BigData
- Publication Year :
- 2019
- Publisher :
- IEEE, 2019.
-
Abstract
- Literature analysis facilitates researchers better understanding the development of science and technology. The conventional literature analysis focuses on the topics, authors, abstracts, keywords, references, etc., and rarely pays attention to the content of papers. In the field of machine learning, the involved methods (M) and datasets (D) are key information in papers. The extraction and mining of M and D are useful for discipline analysis and algorithm recommendation. In this paper, we propose a novel entity recognition model, called MDER, and constructe datasets from the papers of the PAKDD conferences (2009-2019). Some preliminary experiments are conducted to assess the extraction performance and the mining results are visualized.
- Subjects :
- Information retrieval
Computer science
Key (cryptography)
Field (computer science)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2019 IEEE International Conference on Big Data (Big Data)
- Accession number :
- edsair.doi...........01378075cc1bc8588a716da9b1e390a9