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Proceedings of the 31st ACM International Conference on Information & Knowledge Management
ACM
Angol nyelvű Konferenciakötet (Könyv) Tudományos
Megjelent: Association for Computing Machinery (ACM), New York, Amerikai Egyesült Államok
2022
Konferencia:
31st ACM International Conference on Information and Knowledge Management (CIKM 2022) 2022-10-17 [Atlanta, Amerikai Egyesült Államok]
Azonosítók
MTMT: 33168281
DOI:
10.1145/3511808
ISBN:
9781450392365
Fejezetek
Bibas Koby et al. Collaborative Image Understanding. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 77-87
Le Binh et al. Samba: Identifying Inappropriate Videos for Young Children on YouTube. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 88-97
Burgdorf Andreas et al. DocSemMap 2.0: Semantic Labeling based on Textual Data Documentations Using Seq2Seq Context Learner. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 98-107
Cai Xiaoyu et al. Memory Graph with Message Rehearsal for Multi-Turn Dialogue Generation. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 108-117
Cugny Robin et al. AutoXAI: A Framework to Automatically Select the Most Adapted XAI Solution. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 315-324
Ge Zhiqi et al. Consistent, Balanced, and Overlapping Label Trees for Extreme Multi-label Learning. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 551-560
Li Zhuoming et al. Dynamic Network Embedding via Temporal Path Adjacency Matrix Factorization. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 1219-1228
Ma Changsheng et al. DEMO: Disentangled Molecular Graph Generation via an Invertible Flow Model. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 1420-1429
Oh S. et al. Rank List Sensitivity of Recommender Systems to Interaction Perturbations. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 1584-1594
Wu Ensen et al. RelpNet: Relation-based Link Prediction Neural Network. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2138-2147
Wu J. et al. Leveraging Multiple Types of Domain Knowledge for Safe and Effective Drug Recommendation. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2169-2178
Meihan W. et al. FedCDR: Federated Cross-Domain Recommendation for Privacy-Preserving Rating Prediction. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2179-2188
Xu Wanyue et al. Effects of Stubbornness on Opinion Dynamics. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2321-2330
Zhang Jiazheng et al. Dismantling Complex Networks by a Neural Model Trained from Tiny Networks. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2559-2568
Zhang Yao et al. RuDi: Explaining Behavior Sequence Models by Automatic Statistics Generation and Rule Distillation. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2651-2660
Zhou Cangqi et al. End-to-end Modularity-based Community Co-partition in Bipartite Networks. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2711-2720
Zhou Menghui et al. Multi-task Learning with Adaptive Global Temporal Structure for Predicting Alzheimer's Disease Progression. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2743-2752
Benjamin Roy et al. Graph Neural Networks Pretraining Through Inherent Supervision for Molecular Property Prediction. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2903-2912
Cao Lele et al. Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 2954-2963
Li Tong et al. Predicting Multi-level Socioeconomic Indicators from Structural Urban Imagery. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 3282-3291
Rozemberczki Benedek et al. MOOMIN: Deep Molecular Omics Network for Anti-Cancer Drug Combination Therapy. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 3472-3483
Xia Deguo et al. DuARUS: Automatic Geo-object Change Detection with Street-view Imagery for Updating Road Database at Baidu Maps. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 3565-3574
Colomba Luca et al. A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 3893-3897
Louis Paul et al. Sampling Enclosing Subgraphs for Link Prediction. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4269-4273
Lu Yihang et al. Scalable Multiple Kernel k-means Clustering. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4279-4283
Lu Yihang et al. Self-Paced and Discrete Multiple Kernel k-Means. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4284-4288
Moscati Marta et al. Music4All-Onion - A Large-Scale Multi-Faceted Content-Centric Music Recommendation Dataset. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4339-4343
Oh S. et al. Implicit Session Contexts for Next-Item Recommendations. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4364-4368
Podo Luca et al. Plotly.plus, an Improved Dataset for Visualization Recommendation. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4384-4388
Song Junho et al. ST-GAT: A Spatio-Temporal Graph Attention Network for Accurate Traffic Speed Prediction. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4500-4504
Ziaeinejad S. et al. SEERa: A Framework for Community Prediction. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4762-4766
Kovács Ádám et al. POTATO: exPlainable infOrmation exTrAcTion framewOrk. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 4897-4901
Yang Linglin et al. gCBO: A Cost-based Optimizer for Graph Databases. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 5054-5058
Kaiping Zheng et al. eDental: Managing Your Dental Care in Diet Diaries. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 5059-5063
Lee G. et al. Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 5144-5147
Lee Geon et al. Mining of Real-world Hypergraphs: Patterns, Tools, and Generators. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 5144-5147
Yang Zhou et al. Tutorial on Deep Learning Interpretation: A Data Perspective. (2022) Megjelent: Proceedings of the 31st ACM International Conference on Information & Knowledge Management pp. 5156-5159
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2026-10-18 00:04
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