rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data Mining and Big Data
    sub title: 7th International Conference, DMBD 2022, Beijing, China, November 21-24, 2022, Proceedings, Part I
  name:
    name part: Tan, Ying.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Shi, Yuhui.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: si
    date issued: 2022
    edition: 1st ed. 2022.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XX, 435 pages 142 illustrations, 115 illustrations in color)
  abstract: This two-volume set, CCIS 1744 and CCIS 1745 book constitutes the 7th International Conference, on Data Mining and Big Data, DMBD 2022, held in Beijing, China, in November 21-24, 2022. The 62 full papers presented in this two-volume set included in this book were carefully reviewed and selected from 135 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, et cetera.
  table of contents: Deep Reinforcement Learning Approach -- Heterogeneous Multi-unit Control with Curriculum Learning for Multi-agent Reinforcement Learning -- A Deep Reinforcement Learning Approach for Cooperative Target Defense -- Particle Swarm Based Reinforcement Learning -- User's Permission Reasoning Method Based on Knowledge Graph Reward Guidance Reinforcement Learning in Data Center. - SMPG: Adaptive Soft Update for Masked MADDPG -- Attentive Relational State Representation for Intelligent Joint Operation Simulation -- Graph Neural Networks -- Flow Prediction via Multi-view Spatial-temporal Graph Neural Network -- RotatSAGE: A Scalable Knowledge Graph Embedding Model based on Translation Assumptions and Graph Neural Networks -- Denoise Network Structure for User Alignment across Networks via Graph Structure Learning -- OLPGP: An optimized label propagation-based distributed graph partitioning algorithm -- Deep Neural Networks -- DRGS: Low-Precision Full Quantization of Deep Neural Network with Dynamic Rounding and Gradient Scaling for Object Detection -- Emotion Recognition Based on Multi-scale Convolutional Neural Network -- Pose Sequence Model Using the Encoder-decoder Structure for 3d Pose Estimation -- Research and Analysis of Video-Based Human Pose Estimation -- Action Recognition for Solo-militant Based on ResNet and Rule Matching -- Multiple Residual Quantization of Pruning -- Clustering Methods -- Deep Structured Graph Clustering Network -- Improved Clustering Strategies for Learning Style Identiﬁcation in Massive Open Online Courses -- CSHEM - A Compressed Sensing Based Secure Data Processing Method for Electrical Data -- Prediction Methods -- An Improved Multi-Source Spatiotemporal Data Fusion Model based on the Nearest Neighbor Grids for PM2.5 Concentration Interpolation and Prediction -- Study on the Prediction of Rice Noodle Raw Material Index Content by Deep Feature Fusion -- GAP: Goal-Aware Prediction with Hierarchical Interactive Representation for Vehicle Traje…
  note: edited by Ying Tan, Yuhui Shi.
  subject:
    topic: Application software
  subject:
    topic: Computer engineering
  subject:
    topic: Computer networks
  subject:
    topic: Image processing-Digital techniques
  subject:
    topic: Computer vision
  subject:
    topic: Artificial intelligence
  subject:
    topic: Data structures (Computer science)
  subject:
    topic: Information theory
  subject:
    topic: Computer and Information Systems Applications
  subject:
    topic: Computer Engineering and Networks
  subject:
    topic: Computer Imaging, Vision, Pattern Recognition and Graphics
  subject:
    topic: Artificial Intelligence
  subject:
    topic: Data Structures and Information Theory
  classification: QA76.76.A65
  classification: 005.3
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Communications in Computer and Information Science, 1744
  identifier: 9978-981-19-9297-1
  identifier: 9789811992971
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 230119
    record change date: 20240805183633.6
    record identifier: in00004660633