{"product_id":"data-science-foundations-and-applications-9789819682973","title":"Data Science Foundations and Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Graph Mining.\u003cbr\u003e.- MuCo-KGC: Multi-Context-Aware Knowledge Graph Completion.\u003cbr\u003e.- Tensor-Fused Multi-View Graph Contrastive Learning.\u003cbr\u003e.- FOG: Interpretable Feature-Oriented Graph Neural Networks for Tabular Data  Prediction.\u003cbr\u003e.- High Resolution Image Classification with Rich Text Information Based on Graph Convolution Neural Network.\u003cbr\u003e.- Time Interval Aware Graph Neural Networks for Session-Based Recommendation.\u003cbr\u003e.- SSGNN: Structure-aware Scoring Graph Neural Network for Molecular Representation.\u003cbr\u003e.- Mint: An Efficient and Robust In-Place Update Approach for Graph-based Vector Index.\u003cbr\u003e.- Machine Learning Applications.\u003cbr\u003e.- Advancing Comprehensive Aspect-Based Sentiment Analysis with Generative Models.\u003cbr\u003e.- A Systematic Evaluation of Generative Models on Tabular Transportation Data.\u003cbr\u003e.- SDF-Guided Multi-modal Big Data Road Extraction.\u003cbr\u003e.- Player Movement Predictions Using Team and Opponent Dynamics for Doubles Badminton.\u003cbr\u003e.- Representation Learning.\u003cbr\u003e.- Late Fusion Ensembles for Speech Recognition on Diverse Input Audio Representations.\u003cbr\u003e.- Text Enhancement-based Multimodal Fusion for Video Sentiment Analysis.\u003cbr\u003e.- Advancing Rubric-based Automated Essay Scoring with Multi-View BERT: A Case Study in New Zealand.\u003cbr\u003e.- A Script Event Prediction Method Based on Multi-Level Joint Pretraining and Prompt Fine-Tuning.\u003cbr\u003e.- Scientific\/Business Data Analysis.\u003cbr\u003e.- A Multimodal Fusion Model Leveraging MLP Mixer and Handcrafted Features-based Deep Learning Networks for Facial Palsy Detection.\u003cbr\u003e.- Using Pseudo-Synonyms to Generate Embeddings for Clinical Terms.\u003cbr\u003e.- Corporate Carbon Emission Prediction: Combining Structured and Unstructured Data.\u003cbr\u003e.- GDCK: Efficient Large-Scale Graph Distillation utilizing a Model-free Kernelized Approach.\u003cbr\u003e.- Efficient DNA fragment assembly based on Discrete Slime Mould Algorithm.\u003cbr\u003e.- Multi-Scale Control Model for Network Group Behavior.\u003cbr\u003e.- Can Self Supervision Rejuvenate Similarity-Based Link Prediction?.\u003cbr\u003e.- Managing Data Uncertainty in Automatic Mapping of Clinical Classification Systems.\u003cbr\u003e.- Insomnia Detection Based on Brain State Sleep Trajectories.\u003cbr\u003e.- MCA: Multimodal Contrastive Augmentation for Medical Report Generation.\u003cbr\u003e.- Special Track on Large Language Models.\u003cbr\u003e.-Adapting Large Language Models for Parameter-Efficient Log Anomaly Detection.\u003cbr\u003e.- Bot Wars Evolved: Orchestrating Competing LLMs in a Counterstrike Against Phone Scams.\u003cbr\u003e.- Large Language Models with Multi-Faceted Relation Alignment for User Novel Interest Discovery.\u003cbr\u003e.- Estimating Impact of Behavior Change Messages Using Large Language Models.\u003cbr\u003e.- A Meta-Thinking Approach to Mitigating Linguistic Sycophancy in Vision-Language Models.\u003cbr\u003e.- VisCon-100K: Leveraging Contextual Web Data for Fine-tuning Vision Language Models.\u003cbr\u003e.- TRAWL: Tensor Reduced and Approximated Weights for Large Language Models.\u003cbr\u003e.- DAG-Think-Twice: Causal Structure Guided Elicitation of Causal Reasoning in Large Language Model.\u003cbr\u003e.- GRL-Prompt: Towards Prompts Optimization via Graph-empowered Reinforcement Learning using LLMs’ Feedback.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":51360836714839,"sku":"9789819682973","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/data-science-foundations-and-applications-9789819682973","provider":"Book Curl","version":"1.0","type":"link"}