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Heterogeneous Graph Neural Networks for Large-Scale Bid Keyword Matching [article]

Zongtao Liu, Bin Ma, Quan Liu, Jian Xu, Bo Zheng
2021 pre-print
To address these challenges, we develop a heterogeneous-graph-neural-network-based model for keyword matching named HetMatch, which has been deployed both online and offline at the core sponsored search  ...  Existing methods for keyword matching merely consider modeling relevance based on a single type of relation among ads and keywords, such as query clicks or text similarity, which neglects rich heterogeneous  ...  Motivated by the concerns mentioned above, this paper proposes a Heterogeneous graph neural network for keyword Matching (HetMatch) for e-commerce sponsored search.  ... 
doi:10.1145/3459637.3481926 arXiv:2111.00926v1 fatcat:bhmgxfgndjd5jpb3e5v733ehaa

2014 Index IEEE Transactions on Parallel and Distributed Systems Vol. 25

2015 IEEE Transactions on Parallel and Distributed Systems  
Sun, W., +, TPDS Nov. 2014 3025-3035 Truthful QoS-Aware Spectrum Auction with Spatial Reuse for Large-Scale Networks.  ...  Tang, Shaojie, +, TPDS Jan. 2014 2-11 A Truthful QoS-Aware Spectrum Auction with Spatial Reuse for Large- Scale Networks.  ...  on Homogeneous Multiprocessors. 1510 -1521 In-Network Cache Management and Resource Allocation for Information-Centric Networks.  ... 
doi:10.1109/tpds.2014.2371591 fatcat:qxyljogalrbfficryqjowgv3je

User Response Prediction in Online Advertising [article]

Zhabiz Gharibshah, Xingquan Zhu
2021 arXiv   pre-print
What type of data are available for user response prediction? How to predict user response in a reliable and/or transparent way?  ...  Recent years have witnessed a significant increase in the number of studies using computational approaches, including machine learning methods, for user response prediction.  ...  However, bid units are formed as the atomic units for the combination of a keyword in addition to match type and an ad group.  ... 
arXiv:2101.02342v2 fatcat:clgefamcd5fmbeg5ephizy3zqu

Table of contents

2020 IEEE Transactions on Information Forensics and Security  
He 2706 Enhancing Physical Layer Security of Random Caching in Large-Scale Multi-Antenna Heterogeneous Wireless Networks .................................................... W. W. C. Liu, Y. Fu, T.  ...  Ren 299 Reliability Analysis of Large-Scale Adaptive Weighted Networks ............................................................ .................................................  ... 
doi:10.1109/tifs.2019.2940363 fatcat:hnt75fw6nbduzh2c4x4wxdsey4

A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

Tianxing Wu, Guilin Qi, Cheng Li, Meng Wang
2018 Sustainability  
Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs.  ...  Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications.  ...  Lytras who gave a lot of suggestions on how knowledge graphs impact the implementation of OBOR. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/su10093245 fatcat:wrqgfkwfanfejnffn6nyr4nqbq

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI [article]

Jiangchao Yao, Shengyu Zhang, Yang Yao, Feng Wang, Jianxin Ma, Jianwei Zhang, Yunfei Chu, Luo Ji, Kunyang Jia, Tao Shen, Anpeng Wu, Fengda Zhang (+6 others)
2022 arXiv   pre-print
We also discuss potentials and practical experiences of some on-going advanced edge AI topics including pretraining models, graph neural networks and reinforcement learning.  ...  In this survey, we conduct a systematic review for both cloud and edge AI.  ...  It is practically useful for the acceleration of AI models in face of the expensive loading and offloading cost of large-scale neural networks like PTM.  ... 
arXiv:2111.06061v3 fatcat:5rq6s5s4cvcidblidgahwynp34

ASGrid: autonomic management of hybrid sensor grid systems and applications

Xiaolin Li, Xinxin Liu, Han Zhao, Huanyu Zhao, Nanyan Jiang, Manish Parashar
2009 International Journal of Sensor Networks (IJSNet)  
In this paper, we propose an autonomic management framework (ASGrid) to address the requirements of emerging large-scale applications in hybrid grid and sensor network systems.  ...  aggregation and associative rendezvous mechanisms; (2) Self-optimization through utility-based sensor selection, model-driven hierarchical sensing task scheduling, and auction-based game-theoretic approach for  ...  PlanetLab is a large scale heterogeneous distributed environment composed of interconnected sites on a global scale.  ... 
doi:10.1504/ijsnet.2009.029399 fatcat:oq2jsczvtrf7lby7y3z43tleze

Table of Contents

2018 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA)  
Polarized Circular Sectoral Microstrip Antenna 296 Effects Of Slots On Resonant Frequencies Of A Microstrip Patch Antenna 297 Interference Aware Design Of Noma For Large-Scale 5g Networks 298 Enhancement  ...  disabled 183 Android Application for Object Recognition using Neural Networks for the Visually Impaired. 184 BEHAVIOR ANALYSIS OF VISUALIZATION IMAGES USING DEEP LEARNING APPROACH 185 Multi-Instance  ... 
doi:10.1109/iccubea.2018.8697655 fatcat:jvjgmcrh3fhxtkf4kyydawnkiq

2020 Index IEEE Transactions on Information Forensics and Security Vol. 15

2020 IEEE Transactions on Information Forensics and Security  
., +, TIFS 2020 2069-2080 Computer viruses Reliability Analysis of Large-Scale Adaptive Weighted Networks.  ...  ., +, TIFS 2020 500-511 Reliability Analysis of Large-Scale Adaptive Weighted Networks. Song, B., +, TIFS 2020 651-665 SARA: Secure Asynchronous Remote Attestation for IoT Systems.  ... 
doi:10.1109/tifs.2021.3053735 fatcat:eforexmnczeqzdj3sc2j4yoige

Data-Driven Design-by-Analogy: State of the Art and Future Directions [article]

Shuo Jiang, Jie Hu, Kristin L. Wood, Jianxi Luo
2021 arXiv   pre-print
tools for DbA support.  ...  Recently, the increasingly available design databases and rapidly advancing data science and artificial intelligence technologies have presented new opportunities for developing data-driven methods and  ...  Acknowledgements The authors acknowledge the funding support for this work received from the SUTD-MIT International Design Center and SUTD Data-Driven Innovation Laboratory (DDI,  ... 
arXiv:2106.01592v1 fatcat:2bmwso6n4nf5rpvqcexbry4yky

A Review of the Enabling Methodologies for Knowledge Discovery from Smart Grids Data

Fabrizio De Caro, Amedeo Andreotti, Rodolfo Araneo, Massimo Panella, Antonello Rosato, Alfredo Vaccaro, Domenico Villacci
2020 Energies  
The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications.  ...  analysis in data-rich environments, as feedback for the improvement of the forecasting performances.  ...  Metering Interface ANN Artificial Neural Network CNN Convolutional Neural Network DG Distributed Generation ESN Echo State Network GRU Gated Recurrent Unit KDD Knowledge Discovery Process  ... 
doi:10.3390/en13246579 fatcat:aprmmcla6jayvlwpvsabtno3yu

Information agent technology for the Internet: A survey

Matthias Klusch
2001 Data & Knowledge Engineering  
The vast amount of heterogeneous information sources available in the Internet demands advanced solutions for acquiring, mediating, and maintaining relevant information for the common user.  ...  Keywords: Intelligent agents, semantic information brokering, personal assistants, cooperative information systems, agent-mediated electronic business __________________________________________________  ...  The matching engine of the matchmaker agent contains five different filters for (1) keyword-based context matching, (2) TF-IDF based profile comparison, (3) concept-based similarity matching, (4) type-inference  ... 
doi:10.1016/s0169-023x(00)00049-5 fatcat:pzgmrncj4zdi7ejszxt3d7vkp4

Fog Computing Algorithms: A Survey and Research Opportunities

Shaifali P. Malukani, C. K. Bhensdadia
2021 Applied Computer Systems  
Fog computing offers better services to end users by bringing processing, storage, and networking closer to them.  ...  In the existing literature, a systematic study of architectural designs is widely conducted for various applications. Algorithms are seldom examined. Algorithms play a crucial role in fog computing.  ...  [31] use tabu search based algorithm to obtain a sub-optimal solution for the large scale. A nearly optimal solution is obtained for the small-scale system.  ... 
doi:10.2478/acss-2021-0017 fatcat:wf3pedj7fbddbdfjabz2nugwli

A Survey on Deep Reinforcement Learning for Data Processing and Analytics [article]

Qingpeng Cai, Can Cui, Yiyuan Xiong, Wei Wang, Zhongle Xie, Meihui Zhang
2022 arXiv   pre-print
We cover a large number of topics ranging from fundamental problems in system areas such as tuning and scheduling to important applications such as healthcare and fintech.  ...  Finally, we discuss key challenges and future directions for applying DRL in data processing and analytics.  ...  DRL has also been effective in graph designs (e.g., molecular graph [117] ). However, large-scale graph generation using DRL is difficult and daunting because it involves a huge search space.  ... 
arXiv:2108.04526v3 fatcat:kcusgp7jzfbf7ov5os7gwf2e6i

Modelling the transition to a low-carbon energy supply [article]

Alexander Kell
2021 arXiv   pre-print
A well choreographed low-carbon transition is, therefore, required between all of the heterogenous actors in the system, as opposed to changing the behaviour of a single, centralised actor.  ...  [57] presented a neural network for short term load forecasting. Their neural network consisted of three-layers and used adaptive learning for training.  ...  Neural Networks A neural network can be used in both offline and online cases. In this thesis, we used them for both online and offline.  ... 
arXiv:2111.00987v1 fatcat:cltjuirij5fvfhxeoonaxqrs4m
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