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001436463 020__ $$a9783030757687$$q(electronic bk.)
001436463 020__ $$a3030757684$$q(electronic bk.)
001436463 020__ $$z9783030757670$$q(print)
001436463 0247_ $$a10.1007/978-3-030-75768-7$$2doi
001436463 035__ $$aSP(OCoLC)1250275933
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001436463 1112_ $$aPAKDD (Conference)$$n(25th :$$d2021 :$$cOnline)
001436463 24510 $$aAdvances in knowledge discovery and data mining :$$b25th Pacific-Asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings.$$nPart III /$$cKamal Karlapalem, Hong Cheng, Naren Ramakrishnan, R.K. Agrawal, P. Krishna Reddy, Jaideep Srivastava, Tanmoy Chakraborty (eds.).
001436463 2463_ $$aPAKDD 2021
001436463 264_1 $$aCham :$$bSpringer,$$c2021.
001436463 300__ $$a1 online resource (xxiii, 434 pages) :$$billustrations (some color)
001436463 336__ $$atext$$btxt$$2rdacontent
001436463 337__ $$acomputer$$bc$$2rdamedia
001436463 338__ $$aonline resource$$bcr$$2rdacarrier
001436463 4901_ $$aLecture notes in artificial intelligence
001436463 4901_ $$aLecture notes in computer science ;$$v12714
001436463 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001436463 500__ $$aIncludes author index.
001436463 5050_ $$aRepresentation Learning and Embedding -- Episode Adaptive Embedding Networks for Few-shot Learning -- Universal Representation for Code -- Self-supervised Adaptive Aggregator Learning on Graph -- A Fast Algorithm for Simultaneous Sparse Approximation -- STEPs-RL: Speech-Text Entanglement for Phonetically Sound Representation Learning -- RW-GCN: Training Graph Convolution Networks with biased random walk for Semi-Supervised Classification -- Loss-aware Pattern Inference: A Correction on the Wrongly Claimed Limitations of Embedding Models -- SST-GNN: Simplified Spatio-temporal Traffic forecasting model using Graph Neural Network -- VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning -- Self-supervised Graph Representation Learning with Variational Inference -- Manifold Approximation and Projection by Maximizing Graph Information -- Learning Attention-based Translational Knowledge Graph Embedding via Nonlinear Dynamic Mapping -- Multi-Grained Dependency Graph Neural Network for Chinese Open Information Extraction -- Human-Understandable Decision Making for Visual Recognition -- LightCAKE: A Lightweight Framework for Context-Aware Knowledge Graph Embedding -- Transferring Domain Knowledge with an Adviser in Continuous Tasks -- Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach -- Quality Control for Hierarchical Classification with Incomplete Annotations -- Learning from Data -- Learning Discriminative Features using Multi-label Dual Space -- AutoCluster: Meta-learning Based Ensemble Method for Automated Unsupervised Clustering -- BanditRank: Learning to Rank Using Contextual Bandits -- A compressed and accelerated SegNet for plant leaf disease segmentation: A Differential Evolution based approach -- Meta-Context Transformers for Domain-Specific Response Generation -- A Multi-task Kernel Learning Algorithm for Survival Analysis -- Meta-data Augmentation based Search Strategy through Generative Adversarial Network for AutoML Model Selection -- Tree-Capsule: Tree-Structured Capsule Network for Improving Relation Extraction -- Rule Injection-based Generative Adversarial Imitation Learning for Knowledge Graph Reasoning -- Hierarchical Self Attention Based Autoencoder for Open-Set Human Activity Recognition -- Reinforced Natural Language Inference for Distantly Supervised Relation Classification -- SaGCN: Structure-aware Graph Convolution Network for Document-level Relation Extraction -- Addressing the class imbalance problem in medical image segmentation via accelerated Tversky loss function -- Incorporating Relational Knowledge in Explainable Fake News Detection -- Incorporating Syntactic Information into Relation Representations for Enhanced Relation Extraction.
001436463 506__ $$aAccess limited to authorized users.
001436463 520__ $$aThe 3-volume set LNAI 12712-12714 constitutes the proceedings of the 25th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2021, which was held during May 11-14, 2021. The 157 papers included in the proceedings were carefully reviewed and selected from a total of 628 submissions. They were organized in topical sections as follows: Part I: Applications of knowledge discovery and data mining of specialized data; Part II: Classical data mining; data mining theory and principles; recommender systems; and text analytics; Part III: Representation learning and embedding, and learning from data.
001436463 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed May 10, 2021).
001436463 650_0 $$aData mining$$vCongresses.
001436463 650_0 $$aArtificial intelligence$$vCongresses.
001436463 650_6 $$aExploration de données (Informatique)$$vCongrès.
001436463 650_6 $$aIntelligence artificielle$$vCongrès.
001436463 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001436463 655_7 $$aConference papers and proceedings.$$2lcgft
001436463 655_7 $$aActes de congrès.$$2rvmgf
001436463 655_0 $$aElectronic books.
001436463 7001_ $$aKarlapalem, Kamal,$$eeditor$$0(orcid)0000-0003-2528-7979$$1https://orcid.org/0000-0003-2528-7979
001436463 7001_ $$aCheng, Hong$$c(Engineering teacher),$$eeditor.
001436463 7001_ $$aRamakrishnan, Naren,$$eeditor.
001436463 7001_ $$aAgrawal, R. K.,$$eeditor.
001436463 7001_ $$aReddy, P. Krishna$$q(Polepalli Krishna),$$eeditor$$1https://orcid.org/0000-0003-1238-5174
001436463 7001_ $$aSrivastava, Jaideep,$$eeditor.
001436463 7001_ $$aChakraborty, Tanmoy,$$eeditor$$0(orcid)0000-0002-0210-0369$$1https://orcid.org/0000-0002-0210-0369
001436463 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001436463 830_0 $$aLecture notes in computer science ;$$v12714.
001436463 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001436463 852__ $$bebk
001436463 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-75768-7$$zOnline Access$$91397441.1
001436463 909CO $$ooai:library.usi.edu:1436463$$pGLOBAL_SET
001436463 980__ $$aBIB
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