SFr. 123.00
€ 132.84


bestellen

Artikel-Nr. 41574985


Diesen Artikel in meine
Wunschliste
Diesen Artikel
weiterempfehlen
Diesen Preis
beobachten

Weitersagen:


Herausgeber: 
  • Myra Spiliopoulou
  • Vipin Kumar
  • Joao Gama
  • Longbing Cao
  • Can Wang
  • Xintao Wu
  • Xiangmin Zhou
  • Guansong Pang
  • Data Science: Foundations and Applications - 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Pakdd 2025, Sydney, Nsw, Australia,  
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Juni 2025  
    Genre:  EDV / Informatik 
     
    AdvancedAnalytics / bigdata / dataanalysis / datamining / Dataminingapplications / DataScience / Datasciencefoundations / Decision-SupportSystems
    ISBN:  9789819682973 
    EAN-Code: 
    9789819682973 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D 26 mm 
    Gewicht:  709 gr 
    Seiten:  472 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    .- Graph Mining. .- MuCo-KGC: Multi-Context-Aware Knowledge Graph Completion. .- Tensor-Fused Multi-View Graph Contrastive Learning. .- FOG: Interpretable Feature-Oriented Graph Neural Networks for Tabular Data Prediction. .- High Resolution Image Classification with Rich Text Information Based on Graph Convolution Neural Network. .- Time Interval Aware Graph Neural Networks for Session-Based Recommendation. .- SSGNN: Structure-aware Scoring Graph Neural Network for Molecular Representation. .- Mint: An Efficient and Robust In-Place Update Approach for Graph-based Vector Index. .- Machine Learning Applications. .- Advancing Comprehensive Aspect-Based Sentiment Analysis with Generative Models. .- A Systematic Evaluation of Generative Models on Tabular Transportation Data. .- SDF-Guided Multi-modal Big Data Road Extraction. .- Player Movement Predictions Using Team and Opponent Dynamics for Doubles Badminton. .- Representation Learning. .- Late Fusion Ensembles for Speech Recognition on Diverse Input Audio Representations. .- Text Enhancement-based Multimodal Fusion for Video Sentiment Analysis. .- Advancing Rubric-based Automated Essay Scoring with Multi-View BERT: A Case Study in New Zealand. .- A Script Event Prediction Method Based on Multi-Level Joint Pretraining and Prompt Fine-Tuning. .- Scientific/Business Data Analysis. .- A Multimodal Fusion Model Leveraging MLP Mixer and Handcrafted Features-based Deep Learning Networks for Facial Palsy Detection. .- Using Pseudo-Synonyms to Generate Embeddings for Clinical Terms. .- Corporate Carbon Emission Prediction: Combining Structured and Unstructured Data. .- GDCK: Efficient Large-Scale Graph Distillation utilizing a Model-free Kernelized Approach. .- Efficient DNA fragment assembly based on Discrete Slime Mould Algorithm. .- Multi-Scale Control Model for Network Group Behavior. .- Can Self Supervision Rejuvenate Similarity-Based Link Prediction?. .- Managing Data Uncertainty in Automatic Mapping of Clinical Classification Systems. .- Insomnia Detection Based on Brain State Sleep Trajectories. .- MCA: Multimodal Contrastive Augmentation for Medical Report Generation. .- Special Track on Large Language Models. .-Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection. .- Bot Wars Evolved: Orchestrating Competing LLMs in a Counterstrike Against Phone Scams. .- Large Language Models with Multi-Faceted Relation Alignment for User Novel Interest Discovery. .- Estimating Impact of Behavior Change Messages Using Large Language Models. .- A Meta-Thinking Approach to Mitigating Linguistic Sycophancy in Vision-Language Models. .- VisCon-100K: Leveraging Contextual Web Data for Fine-tuning Vision Language Models. .- TRAWL: Tensor Reduced and Approximated Weights for Large Language Models. .- DAG-Think-Twice: Causal Structure Guided Elicitation of Causal Reasoning in Large Language Model. .- GRL-Prompt: Towards Prompts Optimization via Graph-empowered Reinforcement Learning using LLMs’ Feedback.

      



    Wird aktuell angeschaut...
     

    Zurück zur letzten Ansicht


    AGB | Datenschutzerklärung | Mein Konto | Impressum | Partnerprogramm
    Newsletter | 1Advd.ch RSS News-Feed Newsfeed | 1Advd.ch Facebook-Page Facebook | 1Advd.ch Twitter-Page Twitter
    Forbidden Planet AG © 1999-2026
    Alle Angaben ohne Gewähr
     
    SUCHEN

     
     Kategorien
    Im Sortiment stöbern
    Genres
    Hörbücher
    Aktionen
     Infos
    Mein Konto
    Warenkorb
    Meine Wunschliste
     Kundenservice
    Recherchedienst
    Fragen / AGB / Kontakt
    Partnerprogramm
    Impressum
    © by Forbidden Planet AG 1999-2026