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IEEE/ICACT20220392 Question.2 Questioner: tomayoon@ieee.org 2022-02-15 오전 10:21:14	IEEE/ICACT20220392 Answer.2 Answer by Auhor shenhanji@cnic.cn 2022-02-15 오전 10:21:14
Will you tell us what is the major achievement of this paper, and also what is further study issue from this? Thanks in advance!!	This paper proposed a meta learning classification method based on few-shot samples, called BiLSTM-Ridge regression model, which can recognize and learn the characteristics of high threat log samples through less sample learning, and has better generalization detection ability in new unknown test tasks. Future work includes applying this model to other fields, including high threat sample detection and classification of unmarked logs, and exploring the migration learning of other massive log detection in the cloud environment.

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