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020 _a9783031109898
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024 7 _a10.1007/978-3-031-10989-8
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aKnowledge Science, Engineering and Management
_h[electronic resource] :
_b15th International Conference, KSEM 2022, Singapore, August 6–8, 2022, Proceedings, Part III /
_cedited by Gerard Memmi, Baijian Yang, Linghe Kong, Tianwei Zhang, Meikang Qiu.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXVI, 753 p. 282 illus., 240 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v13370
505 0 _aKnowledge Management with Optimization and Security (KMOS) -- Study on Chinese Named Entity Recognition Based on Dynamic Fusion and Adversarial Training -- Spatial Semantic Learning for Travel Time Estimation -- A Fine-Grained Approach for Vulnerabilities Discovery using Augmented Vulnerability Signatures -- PPBR-FL: a Privacy-preserving and Byzantine-robust Federated Learning System -- GAN-Based Fusion Adversarial Training -- MAST-NER: A Low-Resource Named Entity Recognition Method based on Trigger Pool -- Fuzzy information measures feature selection using descriptive statistics data -- Prompt-Based Self-Training Framework for Few-Shot Named Entity Recognition -- Learning Advisor-Advisee Relationship from Multiplex Network Structure -- CorefDRE: Coref-aware Document-level Relation Extraction -- Single Pollutant Prediction Approach by Fusing MLSTM and CNN -- A Multi-objective Evolutionary Algorithm Based on Multi-layer Network Reduction for Community Detection -- Detection DDoS of attacks based on federated learning with Digital Twin Network -- A Privacy-Preserving Subgraph-Level Federated Graph Neural Network via Differential Privacy.
520 _aThe three-volume sets constitute the refereed proceedings of the 15th International Conference on Knowledge Science, Engineering and Management, KSEM 2022, held in Singapore, during August 6–8, 2022. The 169 full papers presented in these proceedings were carefully reviewed and selected from 498 submissions. The papers are organized in the following topical sections: Volume I: Knowledge Science with Learning and AI (KSLA) Volume II: Knowledge Engineering Research and Applications (KERA) Volume III: Knowledge Management with Optimization and Security (KMOS).
650 0 _aArtificial intelligence.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aComputers.
650 0 _aSocial sciences
_xData processing.
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputing Milieux.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aComputer Application in Social and Behavioral Sciences.
700 1 _aMemmi, Gerard.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aYang, Baijian.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aKong, Linghe.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZhang, Tianwei.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aQiu, Meikang.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031109881
776 0 8 _iPrinted edition:
_z9783031109904
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v13370
856 4 0 _uhttps://doi.org/10.1007/978-3-031-10989-8
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