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34th ACM Web Conference, WWW 2025

作者： Zhang, Xin Cai, Fei Zheng, Jianming Pan, Zhiqiang Chen, Wanyu Chen, Honghui Chen, Chonghao National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China College of Electronic Countermeasures National University of Defense Technology Hefei China

ISBN: (纸本)9798400712746

Dynamic graph link prediction is widely utilized in the complex web of the real world, such as social networks, citation networks, recommendation systems, etc. Recent Transformer-based link prediction methods on dynamic graphs not only fail to model the fine-grained structures such as triangles with the vanilla Transformers in the graph serialization process, but also amplify the imbalanced distribution of graphs because of their over-estimation of high-degree nodes. To tackle these issues, we propose a Topology-aware Transformer on Dynamic Graph (TopDyG) for link prediction, consisting of a topology injected Transformer (Ti-Transformer) and a mutual information learning (Mi-Learning). The Ti-Transformer explores the explicit structure of serialized graphs, capturing the topological features. The Mi-Learning mines the relationship between nodes by modeling the mutual information with a prior knowledge, alleviating the over-estimation of high-degree nodes when applying the Transformer-based models for the dynamic graph link prediction task. Extensive experiments on four public datasets containing both transductive and inductive settings present the superiority of our proposal. In particular, TopDyG presents an improvement of 43.27% and 28.75% against the state-of-the-art baselines in terms of NDCG and Jaccard, respectively. The advantages are especially obvious on the high-density graphs. © 2025 Copyright held by the owner/author(s).

关键词： Dynamic graphs Link prediction Topology Transformer

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A New Method for Sentiment Analysis Using Contextual Auto-Encoders

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Journal of Computer Science & Technology 2018年第6期33卷 1307-1319页

作者： Hanen Ameur Salma Jamoussi Abdelmajid Ben Hamadou Multimedia Information Systems and Advanced Computing Laboratory Sfax University Sfax Technopole Sfa 3021 Tunisia

Sentiment analysis, a hot research topic, presents new challenges for understanding users＇ opinions and judg-ments expressed online. They aim to classify the subjective texts by assigning them a polarity label. In this paper, weintroduce a novel machine learning framework using auto-encoders network to predict the sentiment polarity label at theword level and the sentence level. Inspired by the dimensionality reduction and the feature extraction capabilities of theauto-encoders, we propose a new model for distributed word vector representation ＂PMI-SA＂ using as input pointwise-mutual-information ＂PMI＂ word vectors. The resulted continuous word vectors are combined to represent a sentence. Anunsupervised sentence embedding method, called Contextual Recursive Auto-Encoders ＂CoRAE＂, is also developed forlearning sentence representation. Indeed, CoRAE follows the basic idea of the recursive auto-encoders to deeply composethe vectors of words constituting the sentence, but without relying on any syntactic parse tree. The CoRAE model consistsin combining recursively each word with its context words （neighbors＇ words： previous and next） by considering the wordorder. A support vector machine classifier with fine-tuning technique is also used to show that our deep compositionalrepresentation model CoRAE improves significantly the accuracy of sentiment analysis task. Experimental results demon-strate that CoRAE remarkably outperforms several competitive baseline methods on two databases, namely, Sanders twittercorpus and Facebook comments corpus. The CoRAE model achieves an efficiency of 83.28% with the Facebook dataset and97.57% with the Sanders dataset.

关键词： sentiment analysis recursive auto-encoder stacked auto-encoder pointwise mutual information deep embed-ding representation

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Supporting Elderly Care Through an AI-Driven and FHIR-Based Remote Monitoring System 21st

Supporting Elderly Care Through an AI-Driven and FHIR-Based ...

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21st International Symposium on Distributed computing and Artificial Intelligence, DCAI 2024

作者： Martins, Rafael Pereira, Hugo Corrente, Gustavo Xavier, William Conceição, Luís Freitas, Alberto Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering – Polytechnic of Porto Porto Portugal LASI – Intelligent Systems Associate Laboratory Guimarães Portugal Wiseware Solutions Gafanha da Encarnação Portugal MEDCIDS – Department of Community Medicine Information and Health Decision Sciences Faculty of Medicine University of Porto Porto Portugal CINTESIS@RISE – Center for Health Technology and Services Faculty of Medicine University of Porto Porto Portugal

ISBN: (纸本)9783031809453

An increase in the elderly population has led to a growing demand for constant health care. Remote monitoring of seniors aims to provide more effective care and promote patient independence, whether they live in residential homes, or their own homes supported by a domiciliary care service. It encompasses several issues present in their lives that may benefit from being assisted and monitored remotely. There are many successful studies and products focused on one of these issues, but there are no systems, to the best of our knowledge, that serve as a broad remote monitoring solution for multiple of these topics simultaneously. This paper proposes an architecture for an intelligent health monitoring ecosystem to interact with these various aspects of the elderly’s daily life, including monitoring of vital signs, movement and medication intake, detection of falls, sleep quality analysis, access control, and patient–caregiver communication. This solution will make use of wearables and medication dispensers, and it will securely store all patient-related information into an HL7 FHIR standardized database, from where machine learning models can import data for predicting important information and generating alerts when necessary. Next steps involve the development of this proposed system and testing it with elderly volunteers living in a residential home or subscribed to its domiciliary care services. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Remote patient monitoring

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Continual Reinforcement Learning for Digital Twin Synchronization Optimization

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IEEE Transactions on Mobile computing 2025年

作者： Tong, Haonan Chen, Mingzhe Zhao, Jun Hu, Ye Yang, Zhaohui Liu, Yuchen Yin, Changchuan Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence Beijing Advanced Information Network Laboratory Beijing China College of Computing and Data Science Singapore University of Miami Department of Electrical and Computer Engineering Frost Institute for Data Science and Computing Coral Gables33146 United States University of Miami Department of Industrial and Systems Engineering Coral Gables33146 United States Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China North Carolina State University Department of Computer Science RaleighNC27695 United States Beijing Key Laboratory of Network System Architecture and Convergence China Beijing University of Posts and Telecommunications Beijing Advanced Information Network Laboratory Beijing100876 China

This article investigates the adaptive resource allocation scheme for digital twin (DT) synchronization optimization over dynamic wireless networks. In our considered model, a base station (BS) continuously collects factory physical object state data from wireless devices to build a real-time virtual DT system for factory event analysis. Due to continuous data transmission, maintaining DT synchronization must use extensive wireless resources. To address this issue, a subset of devices is selected to transmit their sensing data, and resource block (RB) allocation is optimized. This problem is formulated as a constrained Markov process (CMDP) problem that minimizes the long-term mismatch between the physical and virtual systems. To solve this CMDP, we first transform the problem into a dual problem that refines RB constraint impacts on device scheduling strategies. We then propose a continual reinforcement learning (CRL) algorithm to solve the dual problem. The CRL algorithm learns a stable policy across historical experiences for quick adaptation to dynamics in physical states and network capacity. Simulation results show that the CRL can adapt quickly to network capacity changes and reduce normalized root mean square error (NRMSE) between physical and virtual states by up to 55.2%, using the same RB number as traditional methods. © 2025 IEEE. All rights reserved.

关键词： Markov processes

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Family of Mutually Uncorrelated Codes for DNA Storage Address Design

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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Design of hybrid model for pervasive systems

Design of hybrid model for pervasive systems

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IADIS International Conference on information systems 2012, IS 2012

作者： Achour, Fatma Jedidi, Anis Gargouri, Faiez Multimedia Information Systems and Advanced Computing Laboratory France

ISBN: (纸本)9789728939687

The ubiquitous computing also called pervasive computing regroups the characteristic of mobile computing and the technique of context-awareness that are flexible, adaptable, and capable of acting autonomously on behalf of users. However, the pervasive computing introduces a variety of software, hardware and users engineering challenges. The pervasive computing modeling is a new research area. We interest to purpose methodology for modeling pervasive systems. This paper provides an overview of proposed model of pervasive information system. This purposed model represents the highest level of abstraction that presents only the general concepts of pervasive system. © 2012 IADIS.

关键词： Ubiquitous computing

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The OWL-S extension for the pervasive system

The OWL-S extension for the pervasive system

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IADIS International Conference on information systems 2013, IS 2013

作者： Achour, Fatma Jedidi, Anis Gargouri, Faiez Multimedia Information Systems and Advanced Computing Laboratory France

ISBN: (纸本)9789728939830

The goal of the semantic web, also known as a third generation, is to improve the web service research, discovery, selection, composition and integration. The pervasive systems correspond to a complete communication framework which allows the communicating objects to recognize and locate automatically. The pervasive system tasks are permitted by the semantic web services. The main interest of our research is to propose an adaptation framework of the application to the pervasive system based on semantic web services. In this paper, we present a part of our research work which represents the description of an OWL-S ontology extension to describe the pervasive system. This extension symbolizes the first level of data description in our pervasive system adaptation. © 2013 IADIS.

关键词： Web services

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Online Contentâ€™s Popularity Metrics: RDF-Based Normalization 20th

Online Contentâ€™s Popularity Metrics: RDF-Based Normaliz...

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20th International Conference on Enterprise information systems, ICEIS 2018

作者： Sebei, Hiba Hadj Taib, Mohamed Ali Ben Aouicha, Mohamed Multimedia InfoRmation Systems and Advanced Computing Laboratory Sfax Tunisia

ISBN: (纸本)9783030261689

Social network websites are mainly constructed around the notion of user identities, as set up on the bases of their profiles, and online generated contents such as texts, videos, photos. Still, while some profiles gain an important position in the network, others do not. Similarly, some online generated contents appear to gain a great deal of attention from the part of users, whereas others are completely ignored. In this context, the notion of profile and online content related popularity has come to the forefront. Additionally, several studies turn out to be focused on the area of popularity associated analysis and prediction. Noteworthy, however, is that the popularity evaluative metrics prove to vary from a social network to another. In this respect, the present work is conceived to deal with such challenges through an advanced proposal whereby a unified presentation of popularity metrics related to each social entity, across several social networks, is put forward. Accordingly, a hierarchical structure of popularity metrics, as enhanced with a particular RDF presentation, is suggested, along with a brief summary of wide range of methods used to analyze such entities related popularities. © 2019, Springer Nature Switzerland AG.

关键词： Social networking (online)

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A framework for people re-identification in multi-camera surveillance systems 14

A framework for people re-identification in multi-camera sur...

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14th International Conference on Cognition and Exploratory Learning in the Digital Age, CELDA 2017

作者： Ammar, Sirine Zaghden, Nizar Neji, Mahmoud MIRACL: Multimedia InfoRmation Systems and Advanced Computing Laboratory Tunisia

ISBN: (纸本)9789898533685

People re-identification has been a very active research topic recently in computer vision. It is an important application in surveillance system with disjoint cameras. This paper is focused on the implementation of a human re-identification system. First the face of detected people is divided into three parts and some soft-biometric traits are extracted from each part. In second step, we can recognize people even if their faces are hidden or they are with back appearance. The features extraction will be carried out according to the overall characteristics of the complete images of different persons. An algorithm that identifies people from their body shape will be developed. A powerful representation of the person based on the characteristics of color, texture and shape as well as different soft-biometric features is suggested. The experiments are carried out on SAIVT-SoftBio database which consists of videos from disjoint surveillance cameras as well as some static image based datasets (MUCT, VIPeR, CVSRP). © 2017.

关键词： Security systems

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