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SGNR: A Social Graph Neural Network Based Interactive Recommendation Scheme for E-Commerce

Tsinghua Science and Technology 2023年第4期28卷 786-798页

作者： Dehua Ma Yufeng Wang Jianhua Ma Qun Jin School of Communications and lnformation Engineering Nanjing University of Posts and TelecommunicationsNanjing 210003China Department the Faculty of Computer and Information SciencesHosei UniversityTokyo 194-0298Japan Networked Information Systems Laboratory Department of Human Informatics and Cognitive SciencesFaculty of Human SciencesWaseda UniversityTokyo 169-8050Japan

Interactive Recommendation(IR)formulates the recommendation as a multi-step decision-making process which can actively utilize the individuals’feedback in multiple steps and optimize the long-term user benefit of *** Reinforcement Learning(DRL)has witnessed great application in IR for ***,user cold-start problem impairs the learning process of the DRL-based recommendation ***,most existing DRL-based recommendations ignore user relationships or only consider the single-hop social relationships,which cannot fully utilize the social *** fact that those schemes can not capture the multiple-hop social relationships among users in IR will result in a sub-optimal *** address the above issues,this paper proposes a Social Graph Neural network-based interactive Recommendation scheme(SGNR),which is a multiple-hop social relationships enhanced DRL *** this framework,the multiple-hop social relationships among users are extracted from the social network via the graph neural network which can sufficiently take advantage of the social network to provide more personalized recommendations and effectively alleviate the user cold-start *** experimental results on two real-world datasets demonstrate that the proposed SGNR outperforms other state-of-the-art DRL-based methods that fail to consider social relationships or only consider single-hop social relationships.

关键词： Interactive Recommendation(IR) Deep Reinforcement Learning(DRL) Graph Neural Network(GNN)

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A Partial Face Encryption in Real World Experiences Based on Features Extraction from Edge Detection

International Journal of Interactive Mobile Technologies

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International Journal of Interactive Mobile Technologies 2023年第7期17卷 69-81页

作者： Azeez, Raghad Abdulaali Jamil, Abeer Salim Mahdi, Mohammed Salih Collage of Education Ibn-Rushed for Human Science University of Baghdad Baghdad Iraq Department of Computer Technology Engineering Al-Mansour University College Baghdad Iraq Business Information College University of Information Technology and Communications Baghdad Iraq

User confidentiality protection is concerning a topic in control and monitoring spaces. In image, user's faces security in concerning with compound information, abused situations, participation on global transmission media and real-world experiences are extremely significant. For minifying the counting needs for vast size of image info and for minifying the size of time needful for the image to be address computationally. consequently, partial encryption userface is picked. This study focuses on a large technique that is designed to encrypt the user's face slightly. Primarily, dlib is utilizing for user-face detection. Susan is one of the top edge detectors with valuable localization characteristics marked edges, is used to extract features vectors from user faces. Moreover, the relevance of the suggested generating key is led to a crucial role in security improvement by producing them as difficult to intruders. According to PSNR values, the recommended encryption algorithms provided an adequate outcome in the encryption, they had a lower encrypting duration and a larger encrypting impact. © 2023,International Journal of Interactive Mobile Technologies. All Rights Reserved.

关键词： Cryptography

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Natural Language Generation in AI: Developing Human-Like Text Through Deep Learning 1

Natural Language Generation in AI: Developing Human-Like Tex...

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1st International Conference on Advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Arabelli, Rajeshwarrao Gupta, Suneet Prakash, Nilima Ali, Zainab School of Engineering SR University Department of Electronics and Communications Engineerin Warangal India School of Computer Science and Engineering Galgotias University Greater Noida India Northcap University Gurugram India Vivekananda Global University Department of Journalism & Mass Communication Jaipur India

ISBN: (纸本)9798331518578

Natural Language Generation (NLG) is a subset of artificial intelligence that has as its goal to develop techniques to synthesize human language. This paper focuses on the finding of NLG as a field of study as well as how it benefitted from ideas such as deep learning. Next, we consider the development of NLG models, from standard Recurrent Neural Networks to Long Short-Term Memory networks and from Transformers like GPT. Transformer models have proven to be magnificent for the NLG as they remove the drawbacks of previous models and have improved the long-range dependencies and have synthesized appropriate topic-based content. This paper assesses the merits and the demerit of these models and the areas where that they are used such as healthcare, content creation and customer care. Transformer models are particularly good at producing high-quality text, for which it comes with severe difficulties though. The research for this paper aims to consider future developments of NLG with regards to scalability and the potential for change across fields. © 2025 IEEE.

关键词： Contrastive Learning

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Sorted Consecutive Occurrence Queries in Substrings

arXiv

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arXiv 2024年

作者： Akram, Waseem Mieno, Takuya Department of Computer Science and Engineering Indian Institute of Technology Kanpur India Department of Computer and Network Engineering University of Electro-Communications Chofu Japan

The string indexing problem is a fundamental computational problem with numerous applications, including information retrieval and bioinformatics. It aims to efficiently solve the pattern matching problem: given a text T of length n for preprocessing and a pattern P of length m as a query, the goal is to report all occurrences of P as substrings of T. Navarro and Thankachan [CPM 2015, Theor. Comput. Sci. 2016] introduced a variant of this problem called the gap-bounded consecutive occurrence query, which reports pairs of consecutive occurrences of P in T such that their gaps (i.e., the distances between them) lie within a query-specified range [g1, g2]. Recently, Bille et al. [FSTTCS 2020, Theor. Comput. Sci. 2022] proposed the top-k close consecutive occurrence query, which reports the k closest consecutive occurrences of P in T, sorted in non-descending order of distance. Both problems are optimally solved in query time with O(n log n)-space data structures. In this paper, we generalize these problems to the range query model, which focuses only on occurrences of P in a specified substring T[a..b] of T. Our contributions are as follows: We propose an O(n log2 n)-space data structure that answers the range top-k consecutive occurrence query in O(|P| + log log n + k) time. We propose an O(n log2+ϵ n)-space data structure that answers the range gap-bounded consecutive occurrence query in O(|P| + log log n + output) time, where ϵ is a positive constant and output denotes the number of outputs. Additionally, as by-products, we present algorithms for geometric problems involving weighted horizontal segments in a 2D plane, which are of independent interest. Copyright © 2024, The Authors. All rights reserved.

关键词： Trees (mathematics)

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Editorial

引用

Computational Geometry: Theory and Applications 2024年 122卷

作者： Bae, Sang Won Okamato, Yoshio Division of Artificial Intelligence and Computer Science Kyonggi University Korea Republic of Department of Computer and Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Japan

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Wireless Federated Learning Over Resource-Constrained Networks: Digital Versus Analog Transmissions

引用

IEEE Transactions on Wireless communications 2024年第10期23卷 14020-14036页

作者： Yao, Jiacheng Xu, Wei Yang, Zhaohui You, Xiaohu Bennis, Mehdi Poor, H. Vincent Southeast University Nanjing210096 China Zhejiang Laboratory Hangzhou311121 China The College of Information Science and Electronic Engineering Zhejiang University Zhejiang Hangzhou310027 China The Center for Wireless Communications Oulu University Oulu90014 Finland The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, i.e., digital and analog ones, are effective solutions. In this paper, we quantitatively compare these two techniques, highlighting their essential differences as well as respectively suitable scenarios. We first examine both digital and analog transmission schemes, together with a unified and fair comparison framework under imbalanced device sampling, strict latency targets, and transmit power constraints. A universal convergence analysis under various imperfections is established for evaluating the performance of FL over wireless networks. These analytical results reveal that the fundamental difference between the digital and analog communications lies in whether communication and computation are jointly designed or not. The digital scheme decouples the communication design from FL computing tasks, making it difficult to support uplink transmission from massive devices with limited bandwidth and hence the performance is mainly communication-limited. In contrast, the analog communication allows over-the-air computation (AirComp) and achieves better spectrum utilization. However, the computation-oriented analog transmission reduces power efficiency, and its performance is sensitive to computation errors from imperfect channel state information (CSI). Furthermore, device sampling for both schemes are optimized and differences in sampling optimization are analyzed. Numerical results verify the theoretical analysis and affirm the superior performance of the sampling optimization. © 2002-2012 IEEE.

关键词： Channel state information

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RIS as a Network Resource: User Multiplexing and Pricing Algorithms 3

RIS as a Network Resource: User Multiplexing and Pricing Alg...

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3rd International Conference on 6G Networking, 6GNet 2024

作者： Papadopoulos, Alexandros Lalas, Antonios Votis, Konstantinos Schmid, Stefan Katsalis, Kostas Liaskos, Christos University of Ioannina Department of Computer Science and Engineering Ioannina Greece Information Technologies Institute CERTH Thessaloniki Greece Aristotle University of Thessaloniki Thessaloniki Greece TU Berlin and Fraunhofer SIT Berlin Germany Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki Greece DOCOMO Communications Laboratory GmbH Munich Germany FORTH Ioannina Greece

ISBN: (纸本)9798350378597

Reconfigurable Intelligent Surfaces (RIS) have the ability to actively control wave propagation through space, enabling the creation of Programmable Wireless Environments (PWEs). This capability allows for the uti-lization and control of previously unexploited resources. However, there is a notable gap in allocating these resources to network users in a way that aligns with the pricing policies of telecommunications stakeholders. This paper considers RIS elements as network resources and describes a pricing policy that links the PWE efficiency of individual users to an optimal method for sharing RIS elements. A specialized policy tailored to this purpose, is designed with a focus on robustness, ensuring its applicability across various RIS functionalities and frequency bands. Its computational efficiency further underscores its viability for deployment in practical scenarios. © 2024 IEEE.

关键词： Costs

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MIRA: A Method of Federated MultI-Task Learning for LaRge LAnguage Models

IEEE Networking Letters

引用

IEEE Networking Letters 2025年

作者： Elbakary, Ahmed Ben Issaid, Chaouki Elbatt, Tamer Seddik, Karim Bennis, Mehdi University of Oulu Finland Department of Electronics and Communications Engineering American University in Cairo Egypt Department of Computer Science and Engineering American University in Cairo Egypt Department of Electronics and Communications Engineering Cairo University Egypt

In this paper, we introduce a method for fine-tuning Large Language Models (LLMs), inspired by Multi-Task learning in a federated manner. Our approach leverages the structure of each client's model and enables a learning scheme that considers other clients' tasks and data distribution. To mitigate the extensive computational and communication overhead often associated with LLMs, we utilize a parameter-efficient fine-tuning method, specifically Low-Rank Adaptation (LoRA), to reduce the number of trainable parameters. Experimental results, with different datasets and models, demonstrate the proposed method's effectiveness compared to existing frameworks for federated fine-tuning of LLMs in terms of global and local performances. The proposed scheme outperforms existing baselines by achieving lower local loss for each client, while maintaining comparable global performance. © 2019 IEEE.

关键词： Federated learning

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Robust Synergetic Observer based Fault-Tolerant Control for Electric Vehicle Applications 50

Robust Synergetic Observer based Fault-Tolerant Control for ...

引用

50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Boumegouas, Mohammed Kabir Billa Kouzi, Katia Trabelsi, Mohamed Iqbal, Atif Birame, Mhamed Shadmand, Mohammad B. Laboratory of Semiconductors and Functional Materials Amar Telidji University of Laghouat Algeria Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait Department of Electrical Engineering Qatar University Doha Qatar Department of Electrical & Computer Engineering University of Illinois ChicagoIL United States

ISBN: (纸本)9781665464543

Speed sensor faults are very common in electric vehicle (EV) applications, often disrupting system performance due to the reliance on speed sensor data by the electric drives. Consequently, fault-tolerant control approaches require robust observer structures capable of functioning effectively during faults, swiftly identifying and reconfiguring failures. Thus, this paper presents a novel fault-tolerant control design leveraging a synergetic observer (SO) to substitute the speed sensor in the event of fault. Comparative analysis with a super-twisting sliding mode observer (ST-SMO) highlights the proposed observer's superior performance in terms of tracking accuracy and ripple reduction. The presented simulation results demonstrate promising performance of the proposed observer for fault-tolerant control in EV applications. © 2024 IEEE.

关键词： Permanent magnets

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Solution of Robust Stochastic Discrete Filtering Problem Based on Minimax Functional Criterion

Solution of Robust Stochastic Discrete Filtering Problem Bas...

引用

2024 International Russian Automation Conference, RusAutoCon 2024

作者： Reshetnikova, Irina V. Marshakov, Daniil V. Sokolov, Sergey V. Moscow Technical University of Communications and Informatics North Caucasus branch Research Department Rostov-on-Don Russia Moscow Technical University of Communications and Informatics North Caucasus branch Department of Information Security Rostov-on-Don Russia Moscow Technical University of Communications and Informatics North Caucasus branch Department of Informatics and Computer Engineering Rostov-on-Don Russia

Currently, the solution to the vast majority of problems of assessing the state of discrete stochastic systems operating in stochastic environments is carried out using algorithms developed on the basis of the discrete Kalman filter. The main disadvantage of such estimation schemes is the need for an accurate a priori description of the probabilistic characteristics of the noise of the object and the interference of its observer, the absence of which leads to divergence of the filtering process. All known modifications of the Kalman filtering scheme ensure the stability of the estimation process only for some special cases, leaving the problem of an a priori description of the operating conditions of real systems as a whole unresolved. In this regard, the paper considers an alternative approach to the synthesis of a stable (robust) stochastic estimation scheme based on the choice of a matrix filtering coefficient from the optimization condition of a minimax functional criterion determined by the most unfavorable class of probabilistic distributions noise of the object and its observer. An advantageous feature of the proposed filter, in addition to its robust properties, is a significantly smaller dimension compared to the Kalman scheme, equal to the dimension of the object, which sharply reduces the amount of computational costs in the practical implementation of the filter. The results of a numerical experiment illustrating the effectiveness of the considered approach are presented. © 2024 IEEE.

关键词： Wiener filtering

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