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001483922 001__ 1483922
001483922 003__ OCoLC
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001483922 020__ $$a9783031466717$$q(electronic bk.)
001483922 020__ $$a3031466713$$q(electronic bk.)
001483922 020__ $$z9783031466700
001483922 0247_ $$a10.1007/978-3-031-46671-7$$2doi
001483922 035__ $$aSP(OCoLC)1407624287
001483922 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCQ
001483922 049__ $$aISEA
001483922 050_4 $$aQA76.9.D343
001483922 08204 $$a006.312$$223/eng/20231107
001483922 1112_ $$aADMA (Conference)$$n(19th :$$d2023 :$$cShenyang Shi, China)
001483922 24510 $$aAdvanced data mining and applications :$$b19th International Conference, ADMA 2023, Shenyang, China, August 21-23, 2023, Proceedings.$$nPart III /$$cXiaochun Yang, Heru Suhartanto, Guoren Wang, Bin Wang, Jing Jiang, Bing Li, Huaijie Zhu, Ningning Cui, editors.
001483922 2463_ $$aADMA 2023
001483922 264_1 $$aCham, Switzerland :$$bSpringer,$$c2023.
001483922 300__ $$a1 online resource (xxi, 370 pages) :$$billustrations (some color).
001483922 336__ $$atext$$btxt$$2rdacontent
001483922 337__ $$acomputer$$bc$$2rdamedia
001483922 338__ $$aonline resource$$bcr$$2rdacarrier
001483922 4901_ $$aLecture notes in artificial intelligence
001483922 4901_ $$aLecture notes in computer science ;$$v14178
001483922 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001483922 500__ $$aIncludes author index.
001483922 5050_ $$aPharmaceutical Data Analysis -- Drug-target interaction prediction based on drug subgraph fingerprint extraction strategy and subgraph attention mechanism -- Soft Prompt Transfer for Zero-Shot and Few-Shot Learning in EHR Understanding -- Graph Convolution Synthetic Transformer for Chronic Kidney Disease Onset Prediction -- MTFL: Multi-task feature learning with joint correlation structure learning for Alzheimer’s disease cognitive performance prediction -- Multi-Level Transformer for Cancer Outcome Prediction in Large-Scale Claims Data -- Individual Functional Network Abnormalities Mapping via Graph Representation-based Neural Architecture Search -- A novel application of a mutual information measure for analysing temporal changes in healthcare network graphs -- Drugs Resistance Analysis from Scarce Health Records via Multi-task Graph Representation -- Text Classification -- ParaNet:Parallel Networks with Pre-trained Models for Text Classification -- Open Text Classification Based on Dynamic Boundary Balance -- A Prompt Tuning Method for Chinese Medical Text Classification -- TabMentor: Detect Errors on Tabular Data with Noisy Labels -- Label-aware Hierarchical Contrastive Domain Adaptation for Cross-network Node Classification -- Semi-supervised classification based on Graph Convolution Encoder Representations from BERT -- Global Balanced Text Classification for Stable Disease Diagnosis -- Graph -- Dominance Maximization in Uncertain Graphs -- LAGCL: Towards Stable and Automated Graph Contrastive Learning -- Discriminative Graph-level Anomaly Detection via Dual-students-teacher Model -- Common-Truss-based Community Search on Multilayer Graphs -- Learning To Predict Shortest Path Distance -- Efficient Regular Path Query Evaluation with Structural Path Constraints.EnSpeciVAT: Enhanced SpeciVAT for Cluster Tendency Identification in Graphs -- Pessimistic Adversarially Regularized Learning for Graph Embedding -- M2HGCL: Multi-Scale Meta-Path Integrated Heterogeneous Graph Contrastive Learning.
001483922 506__ $$aAccess limited to authorized users.
001483922 520__ $$aThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21-23, 2023. The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
001483922 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 7, 2023).
001483922 650_6 $$aExploration de données (Informatique)$$vCongrès.
001483922 650_0 $$aData mining$$vCongresses.$$vCongresses$$0(DLC)sh2008102035
001483922 655_0 $$aElectronic books.
001483922 7001_ $$aYang, Xiaochun$$c(College teacher),$$eeditor.
001483922 7001_ $$aSuhartanto, Heru,$$eeditor.
001483922 7001_ $$aWang, Guoren,$$d1966-$$eeditor.
001483922 7001_ $$aWang, Bin,$$eeditor.
001483922 7001_ $$aJiang, Jing,$$eeditor.$$0(OCoLC)oca00642098
001483922 7001_ $$aLi, Bing,$$eeditor.$$0(DNLM)1645049
001483922 7001_ $$aZhu, Huaijie,$$eeditor.
001483922 7001_ $$aCui, Ningning,$$eeditor.
001483922 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001483922 830_0 $$aLecture notes in computer science ;$$v14178.
001483922 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001483922 852__ $$bebk
001483922 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-46671-7$$zOnline Access$$91397441.1
001483922 909CO $$ooai:library.usi.edu:1483922$$pGLOBAL_SET
001483922 980__ $$aBIB
001483922 980__ $$aEBOOK
001483922 982__ $$aEbook
001483922 983__ $$aOnline
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