{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T14:14:26Z","timestamp":1753884866313,"version":"3.41.2"},"reference-count":26,"publisher":"World Scientific Pub Co Pte Ltd","issue":"16","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2021,12,30]]},"abstract":"<jats:p> It draws researchers\u2019 attentions how to make use of the log data effectively without paying much for storing them. In this paper, we propose pattern-based deep learning method to extract the features from log datasets and to facilitate its further use at the reasonable expense of the storage performances. By taking the advantages of the neural network and thoughts to combine statistical features with experts\u2019 knowledge, there are satisfactory results in the experiments on some specified datasets and on the routine systems that our group maintains. Processed on testing data sets, the model is 5%, at least, more likely to outperform its competitors in accuracy perspective. More importantly, its schema unveils a new way to mingle experts\u2019 experiences with statistical log parser. <\/jats:p>","DOI":"10.1142\/s0218126621502960","type":"journal-article","created":{"date-parts":[[2021,6,28]],"date-time":"2021-06-28T08:36:29Z","timestamp":1624869389000},"source":"Crossref","is-referenced-by-count":1,"title":["Pattern-Based Deep Learning Method to Extract Information from the Log Dataset"],"prefix":"10.1142","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9199-8026","authenticated-orcid":false,"given":"Xi","family":"Li","sequence":"first","affiliation":[{"name":"College of Computer Technology, Wuhan Institute of Shipbuilding Technology, 169 Qintai Avenue, Hanyang, Wuhan, Hubei 430050, P. R. China"}]},{"given":"Ting","family":"Wang","sequence":"additional","affiliation":[{"name":"Intelligent Software Technology and Application Research Center, Advanced Institute of Information Technology Peking University, 233 Yonghui Avenue, Xiaoshan, Hangzhou, Zhejiang 311200, P. R. China"}]},{"given":"Shexiong","family":"Wang","sequence":"additional","affiliation":[{"name":"Basic Course Department, Wuhan Donghu University, 301 WenHua Avenue, Jiangxia, Wuhan, Hubei 430212, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2021,6,25]]},"reference":[{"key":"S0218126621502960BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2019.2963301"},{"key":"S0218126621502960BIB002","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2018.2873239"},{"key":"S0218126621502960BIB003","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.2967768"},{"first-page":"117","volume-title":"Proc. ACM SIGOPS 22nd Symp. 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