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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
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072 7 _aUYQ
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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
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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.
_93407
650 0 _aComputer engineering.
_910164
650 0 _aComputer networks .
_931572
650 0 _aComputers.
_98172
650 0 _aSocial sciences
_xData processing.
_983360
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Engineering and Networks.
_9117929
650 2 4 _aComputing Milieux.
_955441
650 2 4 _aComputer Engineering and Networks.
_9117929
650 2 4 _aComputer Application in Social and Behavioral Sciences.
_931815
700 1 _aMemmi, Gerard.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9117930
700 1 _aYang, Baijian.
_eeditor.
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_9117931
700 1 _aKong, Linghe.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9117932
700 1 _aZhang, Tianwei.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9117933
700 1 _aQiu, Meikang.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9117934
710 2 _aSpringerLink (Online service)
_9117935
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
_9117936
856 4 0 _uhttps://doi.org/10.1007/978-3-031-10989-8
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