Knowledge Science, Engineering and Management: Lecture Notes in Computer Science, cartea 14119
Editat de Zhi Jin, Yuncheng Jiang, Robert Andrei Buchmann, Yaxin Bi, Ana-Maria Ghiran, Wenjun Maen Limba Engleză Paperback – 10 aug 2023
| Toate formatele și edițiile | Preț | Express |
|---|---|---|
| Paperback (4) | 522.59 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 522.59 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 523.60 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 523.81 lei 6-8 săpt. | |
| Springer – 10 aug 2023 | 524.20 lei 6-8 săpt. |
Din seria Lecture Notes in Computer Science
- 20%
Preț: 558.53 lei - 20%
Preț: 571.88 lei - 20%
Preț: 675.83 lei - 20%
Preț: 1020.28 lei - 20%
Preț: 620.33 lei - 20%
Preț: 560.93 lei - 20%
Preț: 633.70 lei - 20%
Preț: 678.21 lei - 20%
Preț: 1359.66 lei - 20%
Preț: 560.93 lei - 20%
Preț: 733.68 lei - 20%
Preț: 793.92 lei - 15%
Preț: 558.12 lei - 20%
Preț: 793.92 lei - 20%
Preț: 560.93 lei - 20%
Preț: 748.63 lei - 20%
Preț: 562.49 lei - 20%
Preț: 1246.46 lei - 20%
Preț: 449.81 lei - 20%
Preț: 556.96 lei - 20%
Preț: 562.49 lei - 20%
Preț: 851.78 lei - 20%
Preț: 313.10 lei - 18%
Preț: 945.44 lei - 20%
Preț: 314.86 lei - 20%
Preț: 560.93 lei - 20%
Preț: 313.87 lei - 20%
Preț: 1033.45 lei - 20%
Preț: 563.29 lei - 20%
Preț: 733.68 lei - 20%
Preț: 1137.10 lei - 20%
Preț: 735.28 lei - 20%
Preț: 1079.23 lei - 20%
Preț: 560.11 lei - 20%
Preț: 791.54 lei - 15%
Preț: 672.87 lei - 20%
Preț: 1032.47 lei - 20%
Preț: 617.17 lei - 20%
Preț: 1022.15 lei - 20%
Preț: 984.64 lei - 20%
Preț: 620.33 lei - 20%
Preț: 979.25 lei - 20%
Preț: 402.28 lei - 20%
Preț: 316.28 lei - 20%
Preț: 636.06 lei - 20%
Preț: 320.24 lei - 20%
Preț: 328.94 lei
Preț: 522.59 lei
Preț vechi: 653.24 lei
-20%
Puncte Express: 784
Preț estimativ în valută:
92.40€ • 106.79$ • 79.83£
92.40€ • 106.79$ • 79.83£
Carte tipărită la comandă
Livrare economică 04-18 mai
Specificații
ISBN-13: 9783031402883
ISBN-10: 303140288X
Pagini: 464
Ilustrații: XXIV, 438 p. 120 illus., 115 illus. in color.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.7 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 303140288X
Pagini: 464
Ilustrații: XXIV, 438 p. 120 illus., 115 illus. in color.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.7 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Knowledge Management Systems.- Explainable Multi-type Item Recommendation System based on Knowledge Graph.- A 2D Entity Pair Tagging Scheme for Relation Triplet Extraction.- MVARN: Multi-view attention relation network for figure question answering.- MAGNN-GC: Multi-Head Attentive Graph Neural Networks with Global Context for Session-based Recommendation.- Chinese Relation Extraction with Bi-directional Context-based Lattice LSTM.- MA-TGNN: Multiple Aggregators Graph-Based Model for Text Classification.- Multi-Display Graph Attention Network for Text Classification.- Debiased Contrastive Loss for Collaborative Filtering.- ParaSum: Contrastive Paraphrasing for Low-resource Extractive Text Summarization.- Degree-aware embedding and Interactive feature fusion-based Graph Convolution Collaborative Filtering.- Hypergraph Enhanced Contrastive Learningfor News Recommendation.- Reinforcement Learning-Based Recommendation with User Reviews on Knowledge Graphs.- A Session Recommendation Model based on Heterogeneous Graph Neural Network.- Dialogue State Tracking with a Dialogue-aware Slot-Level Schema Graph Approach.- FedDroidADP: An Adaptive Privacy-Preserving Framework for Federated-Learning-based Android Malware Classification System.- Multi-level and Multi-interest User Interest Modeling for News Recommendation.- CoMeta: Enhancing Meta Embeddings with Collaborative Information in Cold-start Problem of Recommendation.- A Graph Neural Network for Cross-Domain Recommendation Based on Transfer and Inter-Domain Contrastive Learning.- A Hypergraph Augmented and Information Supplementary Network for Session-based Recommendation.- Candidate-aware Attention Enhanced Graph Neural Network for News Recommendation.- Heavy Weighting for Potential Important Clauses.- Knowledge-Aware Two-Stream Decoding for Outline-Conditioned Chinese Story Generation.- Multi-Path based Self-Adaptive Cross-Lingual Summarization.- Temporal Repetition Counting Based on Multi-Stride Collaboration.- Multi-layer Attention Social Recommendation System based on Deep Reinforcement Learning.- SPOAHA: Spark program optimizer based on Artificial Hummingbird Algorithm.- TGKT-based Personalized Learning Path Recommendation with Reinforcement Learning.- Fusion High-Order information with Nonnegative Matrix Factorization Based Community Infomax for Community Detection.- Multi-task learning based skin segmentation.- User Feedback-based Counterfactual Data Augmentation for Sequential Recommendation.- Citation Recommendation Based on Knowledge Graph and Multi-task Learning.- A Pairing Enhancement Approach for AspectSentiment Triplet Extraction.- The Minimal Negated Model Semantics of Assumable Logic Programs.- MT-BICN: Multi-task Balanced Information Cascade Network for Recommendation.