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001483923 001__ 1483923
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001483923 020__ $$a9783031466748$$q(electronic bk.)
001483923 020__ $$a3031466748$$q(electronic bk.)
001483923 020__ $$z9783031466731
001483923 0247_ $$a10.1007/978-3-031-46674-8$$2doi
001483923 035__ $$aSP(OCoLC)1407624487
001483923 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dOCLCO$$dOCLCQ
001483923 049__ $$aISEA
001483923 050_4 $$aQA76.9.D343
001483923 08204 $$a006.312$$223/eng/20231107
001483923 1112_ $$aADMA (Conference)$$n(19th :$$d2023 :$$cShenyang Shi, China)
001483923 24510 $$aAdvanced data mining and applications :$$b19th International Conference, ADMA 2023, Shenyang, China, August 21-23, 2023, Proceedings.$$nPart IV /$$cXiaochun Yang, Heru Suhartanto, Guoren Wang, Bin Wang, Jing Jiang, Bing Li, Huaijie Zhu, Ningning Cui, editors.
001483923 2463_ $$aADMA 2023
001483923 264_1 $$aCham :$$bSpringer,$$c2023.
001483923 300__ $$a1 online resource (xxiii, 697 pages) :$$billustrations (some color).
001483923 336__ $$atext$$btxt$$2rdacontent
001483923 337__ $$acomputer$$bc$$2rdamedia
001483923 338__ $$aonline resource$$bcr$$2rdacarrier
001483923 4901_ $$aLecture notes in artificial intelligence
001483923 4901_ $$aLecture notes in computer science ;$$v14179
001483923 4901_ $$aLNCS sublibrary, SL 7,  Artificial intelligence
001483923 500__ $$aIncludes author index.
001483923 5050_ $$aDeep Learning -- TeaE: an Efficient Method for Improving the Precision of Teaching Evaluation -- Graph Fusion Multimodal Named Entity Recognition Based on Auxiliary Relation Enhancement -- Sentence-level Event Detection without Triggers via Prompt Learning and Machine Reading Comprehension -- Multi-grained Logical Graph Network for Reasoning-based Machine Reading Comprehension -- Adaptive Prototype Learning with Common and Discriminative Features for Few-shot Relation Extraction -- Fine-grained Knowledge Enhancement for Empathetic Dialogue Generation -- Implicit Sentiment Extraction using Structure Generation with Sentiment Instructor Prompt Template -- SE-Prompt: Exploring Semantic Enhancement with Prompt Tuning for Relation Extraction -- Self-supervised Multi-view Clustering Framework with Graph Filtering and Contrast Fusion -- Semantic Selection and Multi-view Alignment for Image-Text Retrieval -- Voice Conversion with Denoising Diffusion Probabilistic GAN Models -- Symbolic & Acoustic: Multi-domain Music Emotion Modeling for Instrumental Music -- Document-level Relation Extraction with Relational Reasoning and Heterogeneous Graph Neural Networks -- A Chinese Named Entity Recognition Method based on Textual Information Perception Fusion -- Aspect-Based Sentiment Analysis via BERT and Multi-Scale CBAM -- A novel adaptive distribution distance-based feature selection method for video traffic identification -- SVIM: a Skeleton-based View-invariant Method for Online Gesture Recognition -- A Unified Information Diffusion Prediction Model based on Multi-task Learning -- Learning Knowledge Representation with Entity Concept Information -- Domain Adaptive Pre-trained Model for Mushroom Image Classification -- Training Noise Robust Deep Neural Networks with Self-supervised Learning -- Path integration enhanced graph attention network -- Graph Contrastive Learning with Hybrid Noise Augmentation for Recommendation -- User-Oriented Interest Representation on Knowledge Graph for Long-Tail Recommendation -- Multi-Self-Supervised Light Graph Convolution Network for Social Recommendation -- A Poisoning Attack Based on Variant Generative Adversarial Networks in Recommender Systems -- Label Correlation guided Feature Selection for Multi-label Learning -- Iterative Encode-and-Decode Graph Neural Network -- Community Detection in Temporal Biological Metabolic Networks based on Semi-NMF Method with Node Similarity Fusion -- UKGAT: Uncertain Knowledge Graph Embedding Enriched KGAT for Recommendation -- Knowledge Graph Link Prediction Model Based on Attention Graph Convolutional Network -- Knowledge Graph Embedding with Relation Rotation and Entity Adjustment by Quaternions -- Towards time-variant-aware Link Prediction in Dynamic Graph through Self-supervised Learning -- Adaptive Heterogeneous graph Contrastive clustering with Multi-Similarity -- Multi-Teacher Local Semantic Distillation from Graph Neural Networks -- AutoAM: An End-To-End Neural Model for Automatic and Universal Argument Mining -- Rethinking the Evaluation of Deep Neural Network Robustness -- A Visual Interpretation-Based Self-Improved Classification System Using Virtual Adversarial Training -- TSCMR:Two-Stage Cross-Modal Retrieval -- Effi-Emp: An AI based approach towards positive empathic expressions -- Industry Track Papers -- Research on Image Segmentation Algorithm Based on Level Set. Ping Wu ((AVIC Shenyang Aircraft Design & Research Institute) -- Predicting learners’ performance using MOOC clickstream -- A Fine-grained Verification Method for Blockchain Data Based on Merkle Path Sharding -- A Privacy Preserving Method for Trajectory Data Publishing Based on Geo-indistinguishability -- HA-CMNet: A Driver CTR Model for Vehicle-Cargo Matching in O2O Platform -- A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Capability Evaluation of Manufacturing Enterprises -- A method for data exchange and management in the military industry field. Ping Wu ((AVIC Shenyang Aircraft Design & Research Institute) -- Multi-region Quality Assessment based on Spatial-Temporal Community Detection from Computed Tomography Images.
001483923 506__ $$aAccess limited to authorized users.
001483923 520__ $$aThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21-23, 2023. The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
001483923 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed November 7, 2023).
001483923 650_6 $$aExploration de données (Informatique)$$vCongrès.
001483923 650_0 $$aData mining$$vCongresses.$$vCongresses$$0(DLC)sh2008102035
001483923 655_0 $$aElectronic books.
001483923 7001_ $$aYang, Xiaochun$$c(College teacher),$$eeditor.
001483923 7001_ $$aSuhartanto, Heru,$$eeditor.
001483923 7001_ $$aWang, Guoren,$$d1966-$$eeditor.
001483923 7001_ $$aWang, Bin,$$eeditor.
001483923 7001_ $$aJiang, Jing,$$eeditor.$$0(OCoLC)oca00642098
001483923 7001_ $$aLi, Bing,$$eeditor.$$0(DNLM)1645049
001483923 7001_ $$aZhu, Huaijie,$$eeditor.
001483923 7001_ $$aCui, Ningning,$$eeditor.
001483923 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001483923 830_0 $$aLecture notes in computer science ;$$v14179.
001483923 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001483923 852__ $$bebk
001483923 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-46674-8$$zOnline Access$$91397441.1
001483923 909CO $$ooai:library.usi.edu:1483923$$pGLOBAL_SET
001483923 980__ $$aBIB
001483923 980__ $$aEBOOK
001483923 982__ $$aEbook
001483923 983__ $$aOnline
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